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University: University of Waterloo  Language: English

You searched for subject:(reinforcement learning). Showing records 1 – 29 of 29 total matches.

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University of Waterloo

1. Gaurav, Ashish. Safety-Oriented Stability Biases for Continual Learning.

Degree: 2020, University of Waterloo

 Continual learning is often confounded by “catastrophic forgetting” that prevents neural networks from learning tasks sequentially. In the case of real world classification systems that… (more)

Subjects/Keywords: deep learning; continual learning; classification; reinforcement learning

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APA (6th Edition):

Gaurav, A. (2020). Safety-Oriented Stability Biases for Continual Learning. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/15579

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Gaurav, Ashish. “Safety-Oriented Stability Biases for Continual Learning.” 2020. Thesis, University of Waterloo. Accessed July 04, 2020. http://hdl.handle.net/10012/15579.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Gaurav, Ashish. “Safety-Oriented Stability Biases for Continual Learning.” 2020. Web. 04 Jul 2020.

Vancouver:

Gaurav A. Safety-Oriented Stability Biases for Continual Learning. [Internet] [Thesis]. University of Waterloo; 2020. [cited 2020 Jul 04]. Available from: http://hdl.handle.net/10012/15579.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Gaurav A. Safety-Oriented Stability Biases for Continual Learning. [Thesis]. University of Waterloo; 2020. Available from: http://hdl.handle.net/10012/15579

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Waterloo

2. Bhalla, Sushrut. Deep Multi Agent Reinforcement Learning for Autonomous Driving.

Degree: 2020, University of Waterloo

 Deep Learning and back-propagation have been successfully used to perform centralized training with communication protocols among multiple agents in a cooperative Multi-Agent Deep Reinforcement Learning(more)

Subjects/Keywords: Machine Learning; Reinforcement Learning; Multi-Agent Reinforcement Learning

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APA (6th Edition):

Bhalla, S. (2020). Deep Multi Agent Reinforcement Learning for Autonomous Driving. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/15799

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Bhalla, Sushrut. “Deep Multi Agent Reinforcement Learning for Autonomous Driving.” 2020. Thesis, University of Waterloo. Accessed July 04, 2020. http://hdl.handle.net/10012/15799.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Bhalla, Sushrut. “Deep Multi Agent Reinforcement Learning for Autonomous Driving.” 2020. Web. 04 Jul 2020.

Vancouver:

Bhalla S. Deep Multi Agent Reinforcement Learning for Autonomous Driving. [Internet] [Thesis]. University of Waterloo; 2020. [cited 2020 Jul 04]. Available from: http://hdl.handle.net/10012/15799.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Bhalla S. Deep Multi Agent Reinforcement Learning for Autonomous Driving. [Thesis]. University of Waterloo; 2020. Available from: http://hdl.handle.net/10012/15799

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Waterloo

3. Vandenhof, Colin. Asking for Help with a Cost in Reinforcement Learning.

Degree: 2020, University of Waterloo

Reinforcement learning (RL) is a powerful tool for developing intelligent agents, and the use of neural networks makes RL techniques more scalable to challenging real-world… (more)

Subjects/Keywords: reinforcement learning; apprenticeship learning; imitation learning; learning from demonstration; human-in-the-loop; interactive reinforcement learning; deep reinforcement learning; active learning; Reinforcement learning; Active learning

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APA (6th Edition):

Vandenhof, C. (2020). Asking for Help with a Cost in Reinforcement Learning. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/15872

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Vandenhof, Colin. “Asking for Help with a Cost in Reinforcement Learning.” 2020. Thesis, University of Waterloo. Accessed July 04, 2020. http://hdl.handle.net/10012/15872.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Vandenhof, Colin. “Asking for Help with a Cost in Reinforcement Learning.” 2020. Web. 04 Jul 2020.

Vancouver:

Vandenhof C. Asking for Help with a Cost in Reinforcement Learning. [Internet] [Thesis]. University of Waterloo; 2020. [cited 2020 Jul 04]. Available from: http://hdl.handle.net/10012/15872.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Vandenhof C. Asking for Help with a Cost in Reinforcement Learning. [Thesis]. University of Waterloo; 2020. Available from: http://hdl.handle.net/10012/15872

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Waterloo

4. Rasmussen, Daniel. Hierarchical reinforcement learning in a biologically plausible neural architecture.

Degree: 2014, University of Waterloo

 Humans and other animals have an impressive ability to quickly adapt to unfamiliar environments, with only minimal feedback. Computational models have been able to provide… (more)

Subjects/Keywords: neural modelling; reinforcement learning; hierarchical reinforcement learning; computational neuroscience

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APA (6th Edition):

Rasmussen, D. (2014). Hierarchical reinforcement learning in a biologically plausible neural architecture. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/8943

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Rasmussen, Daniel. “Hierarchical reinforcement learning in a biologically plausible neural architecture.” 2014. Thesis, University of Waterloo. Accessed July 04, 2020. http://hdl.handle.net/10012/8943.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Rasmussen, Daniel. “Hierarchical reinforcement learning in a biologically plausible neural architecture.” 2014. Web. 04 Jul 2020.

Vancouver:

Rasmussen D. Hierarchical reinforcement learning in a biologically plausible neural architecture. [Internet] [Thesis]. University of Waterloo; 2014. [cited 2020 Jul 04]. Available from: http://hdl.handle.net/10012/8943.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Rasmussen D. Hierarchical reinforcement learning in a biologically plausible neural architecture. [Thesis]. University of Waterloo; 2014. Available from: http://hdl.handle.net/10012/8943

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Waterloo

5. Milen, Pavlov. Towards Global Reinforcement Learning.

Degree: 2008, University of Waterloo

 Sequential decision making under uncertainty is a ubiquitous problem. In everyday situations we are faced with a series of decisions that aim to maximize the… (more)

Subjects/Keywords: reinforcement; learning; framework

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APA (6th Edition):

Milen, P. (2008). Towards Global Reinforcement Learning. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/3671

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Milen, Pavlov. “Towards Global Reinforcement Learning.” 2008. Thesis, University of Waterloo. Accessed July 04, 2020. http://hdl.handle.net/10012/3671.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Milen, Pavlov. “Towards Global Reinforcement Learning.” 2008. Web. 04 Jul 2020.

Vancouver:

Milen P. Towards Global Reinforcement Learning. [Internet] [Thesis]. University of Waterloo; 2008. [cited 2020 Jul 04]. Available from: http://hdl.handle.net/10012/3671.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Milen P. Towards Global Reinforcement Learning. [Thesis]. University of Waterloo; 2008. Available from: http://hdl.handle.net/10012/3671

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Waterloo

6. Jiang, Ju. A Framework for Aggregation of Multiple Reinforcement Learning Algorithms.

Degree: 2007, University of Waterloo

 Aggregation of multiple Reinforcement Learning (RL) algorithms is a new and effective technique to improve the quality of Sequential Decision Making (SDM). The quality of… (more)

Subjects/Keywords: reinforcement learning; aggregation

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APA (6th Edition):

Jiang, J. (2007). A Framework for Aggregation of Multiple Reinforcement Learning Algorithms. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/2752

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Jiang, Ju. “A Framework for Aggregation of Multiple Reinforcement Learning Algorithms.” 2007. Thesis, University of Waterloo. Accessed July 04, 2020. http://hdl.handle.net/10012/2752.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Jiang, Ju. “A Framework for Aggregation of Multiple Reinforcement Learning Algorithms.” 2007. Web. 04 Jul 2020.

Vancouver:

Jiang J. A Framework for Aggregation of Multiple Reinforcement Learning Algorithms. [Internet] [Thesis]. University of Waterloo; 2007. [cited 2020 Jul 04]. Available from: http://hdl.handle.net/10012/2752.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Jiang J. A Framework for Aggregation of Multiple Reinforcement Learning Algorithms. [Thesis]. University of Waterloo; 2007. Available from: http://hdl.handle.net/10012/2752

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Waterloo

7. Lin, Daiwei. Spatially-Distributed Interactive Behaviour Generation for Architecture-Scale Systems Based on Reinforcement Learning.

Degree: 2020, University of Waterloo

 This thesis is part of the research activities of the Living Architecture System Group (LASG). LASG develops immersive, interactive art sculptures combining concepts of architecture,… (more)

Subjects/Keywords: reinforcement learning; human-robot interaction; architecture-scale

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APA (6th Edition):

Lin, D. (2020). Spatially-Distributed Interactive Behaviour Generation for Architecture-Scale Systems Based on Reinforcement Learning. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/15648

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Lin, Daiwei. “Spatially-Distributed Interactive Behaviour Generation for Architecture-Scale Systems Based on Reinforcement Learning.” 2020. Thesis, University of Waterloo. Accessed July 04, 2020. http://hdl.handle.net/10012/15648.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Lin, Daiwei. “Spatially-Distributed Interactive Behaviour Generation for Architecture-Scale Systems Based on Reinforcement Learning.” 2020. Web. 04 Jul 2020.

Vancouver:

Lin D. Spatially-Distributed Interactive Behaviour Generation for Architecture-Scale Systems Based on Reinforcement Learning. [Internet] [Thesis]. University of Waterloo; 2020. [cited 2020 Jul 04]. Available from: http://hdl.handle.net/10012/15648.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Lin D. Spatially-Distributed Interactive Behaviour Generation for Architecture-Scale Systems Based on Reinforcement Learning. [Thesis]. University of Waterloo; 2020. Available from: http://hdl.handle.net/10012/15648

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Waterloo

8. Gupta, Gaurav. Obedience-based Multi-Agent Cooperation for Sequential Social Dilemmas.

Degree: 2020, University of Waterloo

 We propose a mechanism for achieving cooperation and communication in Multi-Agent Reinforcement Learning (MARL) settings by intrinsically rewarding agents for obeying the commands of other… (more)

Subjects/Keywords: Reinforcement Learning; Cooperation; Multi-Agent Reinforcement Learning; Intrinsic Reward; Cheap-Talk Communication

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APA (6th Edition):

Gupta, G. (2020). Obedience-based Multi-Agent Cooperation for Sequential Social Dilemmas. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/15853

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Gupta, Gaurav. “Obedience-based Multi-Agent Cooperation for Sequential Social Dilemmas.” 2020. Thesis, University of Waterloo. Accessed July 04, 2020. http://hdl.handle.net/10012/15853.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Gupta, Gaurav. “Obedience-based Multi-Agent Cooperation for Sequential Social Dilemmas.” 2020. Web. 04 Jul 2020.

Vancouver:

Gupta G. Obedience-based Multi-Agent Cooperation for Sequential Social Dilemmas. [Internet] [Thesis]. University of Waterloo; 2020. [cited 2020 Jul 04]. Available from: http://hdl.handle.net/10012/15853.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Gupta G. Obedience-based Multi-Agent Cooperation for Sequential Social Dilemmas. [Thesis]. University of Waterloo; 2020. Available from: http://hdl.handle.net/10012/15853

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Waterloo

9. Balakrishnan, Aravind. Closing the Modelling Gap: Transfer Learning from a Low-Fidelity Simulator for Autonomous Driving.

Degree: 2020, University of Waterloo

 The behaviour planning subsystem, which is responsible for high-level decision making and planning, is an important aspect of an autonomous driving system. There are advantages… (more)

Subjects/Keywords: reinforcement learning; autonomous driving; transfer learning; Automated vehicles; Machine learning

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APA (6th Edition):

Balakrishnan, A. (2020). Closing the Modelling Gap: Transfer Learning from a Low-Fidelity Simulator for Autonomous Driving. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/15570

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Balakrishnan, Aravind. “Closing the Modelling Gap: Transfer Learning from a Low-Fidelity Simulator for Autonomous Driving.” 2020. Thesis, University of Waterloo. Accessed July 04, 2020. http://hdl.handle.net/10012/15570.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Balakrishnan, Aravind. “Closing the Modelling Gap: Transfer Learning from a Low-Fidelity Simulator for Autonomous Driving.” 2020. Web. 04 Jul 2020.

Vancouver:

Balakrishnan A. Closing the Modelling Gap: Transfer Learning from a Low-Fidelity Simulator for Autonomous Driving. [Internet] [Thesis]. University of Waterloo; 2020. [cited 2020 Jul 04]. Available from: http://hdl.handle.net/10012/15570.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Balakrishnan A. Closing the Modelling Gap: Transfer Learning from a Low-Fidelity Simulator for Autonomous Driving. [Thesis]. University of Waterloo; 2020. Available from: http://hdl.handle.net/10012/15570

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Waterloo

10. Liang, Jia. Machine Learning for SAT Solvers.

Degree: 2018, University of Waterloo

 Boolean SAT solvers are indispensable tools in a variety of domains in computer science and engineering where efficient search is required. Not only does this… (more)

Subjects/Keywords: Branching heuristic; Restart; Reinforcement learning; Sat solver; Machine learning; Optimization

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APA (6th Edition):

Liang, J. (2018). Machine Learning for SAT Solvers. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/14207

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Liang, Jia. “Machine Learning for SAT Solvers.” 2018. Thesis, University of Waterloo. Accessed July 04, 2020. http://hdl.handle.net/10012/14207.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Liang, Jia. “Machine Learning for SAT Solvers.” 2018. Web. 04 Jul 2020.

Vancouver:

Liang J. Machine Learning for SAT Solvers. [Internet] [Thesis]. University of Waterloo; 2018. [cited 2020 Jul 04]. Available from: http://hdl.handle.net/10012/14207.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Liang J. Machine Learning for SAT Solvers. [Thesis]. University of Waterloo; 2018. Available from: http://hdl.handle.net/10012/14207

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Waterloo

11. Shahidi, Hamidreza. Neural Text Generation from Structured and Unstructured Data.

Degree: 2019, University of Waterloo

 A number of researchers have recently questioned the necessity of increasingly complex neural network (NN) architectures. In particular, several recent papers have shown that simpler,… (more)

Subjects/Keywords: deep learning; reinforcement learning; natural language processing; text generation

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APA (6th Edition):

Shahidi, H. (2019). Neural Text Generation from Structured and Unstructured Data. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/14979

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Shahidi, Hamidreza. “Neural Text Generation from Structured and Unstructured Data.” 2019. Thesis, University of Waterloo. Accessed July 04, 2020. http://hdl.handle.net/10012/14979.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Shahidi, Hamidreza. “Neural Text Generation from Structured and Unstructured Data.” 2019. Web. 04 Jul 2020.

Vancouver:

Shahidi H. Neural Text Generation from Structured and Unstructured Data. [Internet] [Thesis]. University of Waterloo; 2019. [cited 2020 Jul 04]. Available from: http://hdl.handle.net/10012/14979.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Shahidi H. Neural Text Generation from Structured and Unstructured Data. [Thesis]. University of Waterloo; 2019. Available from: http://hdl.handle.net/10012/14979

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Waterloo

12. Ganapathi Subramanian, Sriram. Reinforcement Learning for Determining Spread Dynamics of Spatially Spreading Processes with Emphasis on Forest Fires.

Degree: 2018, University of Waterloo

 Machine learning algorithms have increased tremendously in power in recent years but have yet to be fully utilized in many ecology and sustainable resource management… (more)

Subjects/Keywords: Reinforcement Learning; Machine Learning; Deep Learning; Spatially Spreading Processes; Sustainability; Forest Wildfire Management; A3C

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APA (6th Edition):

Ganapathi Subramanian, S. (2018). Reinforcement Learning for Determining Spread Dynamics of Spatially Spreading Processes with Emphasis on Forest Fires. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/13148

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Ganapathi Subramanian, Sriram. “Reinforcement Learning for Determining Spread Dynamics of Spatially Spreading Processes with Emphasis on Forest Fires.” 2018. Thesis, University of Waterloo. Accessed July 04, 2020. http://hdl.handle.net/10012/13148.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Ganapathi Subramanian, Sriram. “Reinforcement Learning for Determining Spread Dynamics of Spatially Spreading Processes with Emphasis on Forest Fires.” 2018. Web. 04 Jul 2020.

Vancouver:

Ganapathi Subramanian S. Reinforcement Learning for Determining Spread Dynamics of Spatially Spreading Processes with Emphasis on Forest Fires. [Internet] [Thesis]. University of Waterloo; 2018. [cited 2020 Jul 04]. Available from: http://hdl.handle.net/10012/13148.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Ganapathi Subramanian S. Reinforcement Learning for Determining Spread Dynamics of Spatially Spreading Processes with Emphasis on Forest Fires. [Thesis]. University of Waterloo; 2018. Available from: http://hdl.handle.net/10012/13148

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Waterloo

13. Chan, Tsz Kiu. Curiosity-Based Learning Algorithm for Interactive Art Sculptures.

Degree: 2016, University of Waterloo

 This thesis is part of the research activities of the Living Architecture System Group (LASG). Combining techniques in architecture, the arts, electronics, and software, LASG… (more)

Subjects/Keywords: Reinforcement learning; Interactive Arts; Intrinsic Motivation; Embodied Arts

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APA (6th Edition):

Chan, T. K. (2016). Curiosity-Based Learning Algorithm for Interactive Art Sculptures. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/10278

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Chan, Tsz Kiu. “Curiosity-Based Learning Algorithm for Interactive Art Sculptures.” 2016. Thesis, University of Waterloo. Accessed July 04, 2020. http://hdl.handle.net/10012/10278.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Chan, Tsz Kiu. “Curiosity-Based Learning Algorithm for Interactive Art Sculptures.” 2016. Web. 04 Jul 2020.

Vancouver:

Chan TK. Curiosity-Based Learning Algorithm for Interactive Art Sculptures. [Internet] [Thesis]. University of Waterloo; 2016. [cited 2020 Jul 04]. Available from: http://hdl.handle.net/10012/10278.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Chan TK. Curiosity-Based Learning Algorithm for Interactive Art Sculptures. [Thesis]. University of Waterloo; 2016. Available from: http://hdl.handle.net/10012/10278

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

14. Naouach, Mohamed Malek. Towards A Workload-Driven Flow Scheduler For Modern Datacenters.

Degree: 2018, University of Waterloo

 Modern datacenters run different applications with various communication requirements in terms of bandwidth and deadlines. Of particular interest are deadlines that are driving web-search workloads… (more)

Subjects/Keywords: datacenters; flow scheduling; reinforcement learning

…3.2 Actor-critic reinforcement learning problem[44]… …16 3.3 Scheduling flows in Artemis using reinforcement learning . . . . . . . . . . 17… …schedule the arrived flows using a reinforcement-learning loop. In this thesis, we present… …first using the deep reinforcement actorcritic learning model. The applications’ communication… …model flow-scheduling as a deep reinforcement learning problem, and we solve it at the end… 

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APA (6th Edition):

Naouach, M. M. (2018). Towards A Workload-Driven Flow Scheduler For Modern Datacenters. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/13978

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Naouach, Mohamed Malek. “Towards A Workload-Driven Flow Scheduler For Modern Datacenters.” 2018. Thesis, University of Waterloo. Accessed July 04, 2020. http://hdl.handle.net/10012/13978.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Naouach, Mohamed Malek. “Towards A Workload-Driven Flow Scheduler For Modern Datacenters.” 2018. Web. 04 Jul 2020.

Vancouver:

Naouach MM. Towards A Workload-Driven Flow Scheduler For Modern Datacenters. [Internet] [Thesis]. University of Waterloo; 2018. [cited 2020 Jul 04]. Available from: http://hdl.handle.net/10012/13978.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Naouach MM. Towards A Workload-Driven Flow Scheduler For Modern Datacenters. [Thesis]. University of Waterloo; 2018. Available from: http://hdl.handle.net/10012/13978

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Waterloo

15. Abdalrahman, Ahmed. PEV Charging Infrastructure Integration into Smart Grid.

Degree: 2020, University of Waterloo

 Plug-in electric vehicles (PEVs) represent a huge step forward in a green transportation system, contribute to the reduction of greenhouse gas emission, and reduce the… (more)

Subjects/Keywords: PEV charging infrastructure; service differentiation; dynamic pricing; deep reinforcement learning; Capacity planning; Charging facility siting

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APA (6th Edition):

Abdalrahman, A. (2020). PEV Charging Infrastructure Integration into Smart Grid. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/15819

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Abdalrahman, Ahmed. “PEV Charging Infrastructure Integration into Smart Grid.” 2020. Thesis, University of Waterloo. Accessed July 04, 2020. http://hdl.handle.net/10012/15819.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Abdalrahman, Ahmed. “PEV Charging Infrastructure Integration into Smart Grid.” 2020. Web. 04 Jul 2020.

Vancouver:

Abdalrahman A. PEV Charging Infrastructure Integration into Smart Grid. [Internet] [Thesis]. University of Waterloo; 2020. [cited 2020 Jul 04]. Available from: http://hdl.handle.net/10012/15819.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Abdalrahman A. PEV Charging Infrastructure Integration into Smart Grid. [Thesis]. University of Waterloo; 2020. Available from: http://hdl.handle.net/10012/15819

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Waterloo

16. Shokri, Maryam. Oppositional Reinforcement Learning with Applications.

Degree: 2008, University of Waterloo

 Machine intelligence techniques contribute to solving real-world problems. Reinforcement learning (RL) is one of the machine intelligence techniques with several characteristics that make it suitable… (more)

Subjects/Keywords: Reinforcement learning; opposition-based learning; OQ(lambda); NOQ(lambda)

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APA (6th Edition):

Shokri, M. (2008). Oppositional Reinforcement Learning with Applications. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/4040

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Shokri, Maryam. “Oppositional Reinforcement Learning with Applications.” 2008. Thesis, University of Waterloo. Accessed July 04, 2020. http://hdl.handle.net/10012/4040.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Shokri, Maryam. “Oppositional Reinforcement Learning with Applications.” 2008. Web. 04 Jul 2020.

Vancouver:

Shokri M. Oppositional Reinforcement Learning with Applications. [Internet] [Thesis]. University of Waterloo; 2008. [cited 2020 Jul 04]. Available from: http://hdl.handle.net/10012/4040.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Shokri M. Oppositional Reinforcement Learning with Applications. [Thesis]. University of Waterloo; 2008. Available from: http://hdl.handle.net/10012/4040

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

17. Tse, Timmy Rong Tian. Model-Based Bayesian Sparse Sampling for Data Efficient Control.

Degree: 2019, University of Waterloo

 In this work, we propose a novel Bayesian-inspired model-based policy search algorithm for data efficient control. In contrast to other model-based approaches, our algorithm makes… (more)

Subjects/Keywords: machine learning; reinforcement learning; artificial intelligence

…known as Reinforcement Learning (RL) provides a rich and attractive framework to… …approach this problem. The beginnings of Reinforcement Learning date back to the ideas of Bellman… …technique known as model-based Bayesian Reinforcement Learning (BRL). In this… …methods and model-based reinforcement learning such as the Dyna architecture and the model… …becomes what is known as reinforcement learning. 2.2 Reinforcement Learning Reinforcement… 

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APA (6th Edition):

Tse, T. R. T. (2019). Model-Based Bayesian Sparse Sampling for Data Efficient Control. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/14774

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Tse, Timmy Rong Tian. “Model-Based Bayesian Sparse Sampling for Data Efficient Control.” 2019. Thesis, University of Waterloo. Accessed July 04, 2020. http://hdl.handle.net/10012/14774.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Tse, Timmy Rong Tian. “Model-Based Bayesian Sparse Sampling for Data Efficient Control.” 2019. Web. 04 Jul 2020.

Vancouver:

Tse TRT. Model-Based Bayesian Sparse Sampling for Data Efficient Control. [Internet] [Thesis]. University of Waterloo; 2019. [cited 2020 Jul 04]. Available from: http://hdl.handle.net/10012/14774.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Tse TRT. Model-Based Bayesian Sparse Sampling for Data Efficient Control. [Thesis]. University of Waterloo; 2019. Available from: http://hdl.handle.net/10012/14774

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Waterloo

18. Pereira, Sahil. Stackelberg Multi-Agent Reinforcement Learning for Hierarchical Environments.

Degree: 2020, University of Waterloo

 This thesis explores the application of multi-agent reinforcement learning in domains containing asymmetries between agents, caused by differences in information and position, resulting in a… (more)

Subjects/Keywords: reinforcement learning; multi-agent; stackelberg model; hierarchical environments; game theory; machine learning; continuous space; policy gradient; markov games; actor critic

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APA (6th Edition):

Pereira, S. (2020). Stackelberg Multi-Agent Reinforcement Learning for Hierarchical Environments. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/15851

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Pereira, Sahil. “Stackelberg Multi-Agent Reinforcement Learning for Hierarchical Environments.” 2020. Thesis, University of Waterloo. Accessed July 04, 2020. http://hdl.handle.net/10012/15851.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Pereira, Sahil. “Stackelberg Multi-Agent Reinforcement Learning for Hierarchical Environments.” 2020. Web. 04 Jul 2020.

Vancouver:

Pereira S. Stackelberg Multi-Agent Reinforcement Learning for Hierarchical Environments. [Internet] [Thesis]. University of Waterloo; 2020. [cited 2020 Jul 04]. Available from: http://hdl.handle.net/10012/15851.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Pereira S. Stackelberg Multi-Agent Reinforcement Learning for Hierarchical Environments. [Thesis]. University of Waterloo; 2020. Available from: http://hdl.handle.net/10012/15851

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

19. Song, Haobei. Optimal Learning Theory and Approximate Optimal Learning Algorithms.

Degree: 2019, University of Waterloo

 The exploration/exploitation dilemma is a fundamental but often computationally intractable problem in reinforcement learning. The dilemma also impacts data efficiency which can be pivotal when… (more)

Subjects/Keywords: reinforcement learning; machine learning; exploration; exploitation; optimal learning; Bayesian reinforcement learning; model based reinforcement learning; neural network

…2 1.2 Problem space and classes of reinforcement learning algorithms . . . . . . . 4… …11 2.2 A model based reinforcement learning framework (Dyna)… …reinforcement learning problems based on visual input (such as video games)… …45 Architecture of a general stochastic decision process based reinforcement learning… …in partially observable reinforcement learning as a random variable which is a function of… 

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APA (6th Edition):

Song, H. (2019). Optimal Learning Theory and Approximate Optimal Learning Algorithms. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/15042

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Song, Haobei. “Optimal Learning Theory and Approximate Optimal Learning Algorithms.” 2019. Thesis, University of Waterloo. Accessed July 04, 2020. http://hdl.handle.net/10012/15042.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Song, Haobei. “Optimal Learning Theory and Approximate Optimal Learning Algorithms.” 2019. Web. 04 Jul 2020.

Vancouver:

Song H. Optimal Learning Theory and Approximate Optimal Learning Algorithms. [Internet] [Thesis]. University of Waterloo; 2019. [cited 2020 Jul 04]. Available from: http://hdl.handle.net/10012/15042.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Song H. Optimal Learning Theory and Approximate Optimal Learning Algorithms. [Thesis]. University of Waterloo; 2019. Available from: http://hdl.handle.net/10012/15042

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Waterloo

20. Mahootchi, Masoud. Storage System Management Using Reinforcement Learning Techniques and Nonlinear Models.

Degree: 2009, University of Waterloo

 In this thesis, modeling and optimization in the field of storage management under stochastic condition will be investigated using two different methodologies: Simulation Optimization Techniques… (more)

Subjects/Keywords: reinforcement learning; nonlinear models; storage management; reservoir management

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APA (6th Edition):

Mahootchi, M. (2009). Storage System Management Using Reinforcement Learning Techniques and Nonlinear Models. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/4213

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Mahootchi, Masoud. “Storage System Management Using Reinforcement Learning Techniques and Nonlinear Models.” 2009. Thesis, University of Waterloo. Accessed July 04, 2020. http://hdl.handle.net/10012/4213.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Mahootchi, Masoud. “Storage System Management Using Reinforcement Learning Techniques and Nonlinear Models.” 2009. Web. 04 Jul 2020.

Vancouver:

Mahootchi M. Storage System Management Using Reinforcement Learning Techniques and Nonlinear Models. [Internet] [Thesis]. University of Waterloo; 2009. [cited 2020 Jul 04]. Available from: http://hdl.handle.net/10012/4213.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Mahootchi M. Storage System Management Using Reinforcement Learning Techniques and Nonlinear Models. [Thesis]. University of Waterloo; 2009. Available from: http://hdl.handle.net/10012/4213

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

21. Mohammadi Sepahvand, Nazanin. RELPH: A Computational Model for Human Decision Making.

Degree: 2013, University of Waterloo

 The updating process, which consists of building mental models and adapting them to the changes occurring in the environment, is impaired in neglect patients. A… (more)

Subjects/Keywords: computational Modeling; Updating; neglect; reinforcement learning

…43 Figure 16. Reinforcement learning with only a reward signal as an external feedback… …representation of the different learning mechanisms in the brain ............... 40 Figure 14… …Supervised learning with error signal back-propagating to the system as a training signal… …supervised learning in brain… …Figure 17. Unsupervised learning with absolutely no external feedback… 

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APA (6th Edition):

Mohammadi Sepahvand, N. (2013). RELPH: A Computational Model for Human Decision Making. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/7883

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Mohammadi Sepahvand, Nazanin. “RELPH: A Computational Model for Human Decision Making.” 2013. Thesis, University of Waterloo. Accessed July 04, 2020. http://hdl.handle.net/10012/7883.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Mohammadi Sepahvand, Nazanin. “RELPH: A Computational Model for Human Decision Making.” 2013. Web. 04 Jul 2020.

Vancouver:

Mohammadi Sepahvand N. RELPH: A Computational Model for Human Decision Making. [Internet] [Thesis]. University of Waterloo; 2013. [cited 2020 Jul 04]. Available from: http://hdl.handle.net/10012/7883.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Mohammadi Sepahvand N. RELPH: A Computational Model for Human Decision Making. [Thesis]. University of Waterloo; 2013. Available from: http://hdl.handle.net/10012/7883

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Waterloo

22. Tsang, Florence. Learning a Motion Policy to Navigate Environments with Structured Uncertainty.

Degree: 2020, University of Waterloo

 Navigating in uncertain environments is a fundamental ability that robots must have in many applications such as moving goods in a warehouse or transporting materials… (more)

Subjects/Keywords: robot navigation; reinforcement learning; motion planning; Robots – Motion; Uncertainty (Information theory); Robots – Programming; Robots – Control systems.

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APA (6th Edition):

Tsang, F. (2020). Learning a Motion Policy to Navigate Environments with Structured Uncertainty. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/15562

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Tsang, Florence. “Learning a Motion Policy to Navigate Environments with Structured Uncertainty.” 2020. Thesis, University of Waterloo. Accessed July 04, 2020. http://hdl.handle.net/10012/15562.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Tsang, Florence. “Learning a Motion Policy to Navigate Environments with Structured Uncertainty.” 2020. Web. 04 Jul 2020.

Vancouver:

Tsang F. Learning a Motion Policy to Navigate Environments with Structured Uncertainty. [Internet] [Thesis]. University of Waterloo; 2020. [cited 2020 Jul 04]. Available from: http://hdl.handle.net/10012/15562.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Tsang F. Learning a Motion Policy to Navigate Environments with Structured Uncertainty. [Thesis]. University of Waterloo; 2020. Available from: http://hdl.handle.net/10012/15562

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Waterloo

23. Alhussein, Omar. On the Orchestration and Provisioning of NFV-enabled Multicast Services.

Degree: 2020, University of Waterloo

 The paradigm of network function virtualization (NFV) with the support of software-defined networking has emerged as a prominent approach to foster innovation in the networking… (more)

Subjects/Keywords: NFV; 5G networks; multicast services; NF chain embedding; online algorithms; primal-dual scheme; competitive analysis; reinforcement learning

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APA (6th Edition):

Alhussein, O. (2020). On the Orchestration and Provisioning of NFV-enabled Multicast Services. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/15850

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Alhussein, Omar. “On the Orchestration and Provisioning of NFV-enabled Multicast Services.” 2020. Thesis, University of Waterloo. Accessed July 04, 2020. http://hdl.handle.net/10012/15850.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Alhussein, Omar. “On the Orchestration and Provisioning of NFV-enabled Multicast Services.” 2020. Web. 04 Jul 2020.

Vancouver:

Alhussein O. On the Orchestration and Provisioning of NFV-enabled Multicast Services. [Internet] [Thesis]. University of Waterloo; 2020. [cited 2020 Jul 04]. Available from: http://hdl.handle.net/10012/15850.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Alhussein O. On the Orchestration and Provisioning of NFV-enabled Multicast Services. [Thesis]. University of Waterloo; 2020. Available from: http://hdl.handle.net/10012/15850

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

24. Shein, Mariah. A spiking neural network of state transition probabilities in model-based reinforcement learning.

Degree: 2017, University of Waterloo

 The development of the field of reinforcement learning was based on psychological studies of the instrumental conditioning of humans and other animals. Recently, reinforcement learning(more)

Subjects/Keywords: reinforcement learning; model-based reinforcement learning; spiking neural model; state transition probability; decision task

…state transition probabilities used in modelbased reinforcement learning (RL) may be… …informed psychological and neuroscientific studies of human and animal reinforcement learning… …Historical background The basic idea of reinforcement learning has been around for centuries, for… …conditioning to develop the field of reinforcement learning (RL). 1.2 Reinforcement… …learning Central to reinforcement learning (RL) are the terms “state”, “action”, and… 

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APA (6th Edition):

Shein, M. (2017). A spiking neural network of state transition probabilities in model-based reinforcement learning. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/12574

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Shein, Mariah. “A spiking neural network of state transition probabilities in model-based reinforcement learning.” 2017. Thesis, University of Waterloo. Accessed July 04, 2020. http://hdl.handle.net/10012/12574.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Shein, Mariah. “A spiking neural network of state transition probabilities in model-based reinforcement learning.” 2017. Web. 04 Jul 2020.

Vancouver:

Shein M. A spiking neural network of state transition probabilities in model-based reinforcement learning. [Internet] [Thesis]. University of Waterloo; 2017. [cited 2020 Jul 04]. Available from: http://hdl.handle.net/10012/12574.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Shein M. A spiking neural network of state transition probabilities in model-based reinforcement learning. [Thesis]. University of Waterloo; 2017. Available from: http://hdl.handle.net/10012/12574

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

25. Li, Changjian. Autonomous Driving: A Multi-Objective Deep Reinforcement Learning Approach.

Degree: 2019, University of Waterloo

 Autonomous driving is a challenging domain that entails multiple aspects: a vehicle should be able to drive to its destination as fast as possible while… (more)

Subjects/Keywords: autonomous driving; reinforcement learning; Markov decision process; deep learning

…1 Introduction 1.1 Motivation Deep reinforcement learning [33] has seen some… …of Go [52], reinforcement learning (RL) offers an intriguing promise… …Overview Reinforcement learning dates back to the research on optimal control, psychology and… …developed for reinforcement learning, namely the value function approaches and the policy gradient… …x5D; have recently been shown to be a promising direction for reinforcement learning. Multi… 

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APA (6th Edition):

Li, C. (2019). Autonomous Driving: A Multi-Objective Deep Reinforcement Learning Approach. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/14697

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Li, Changjian. “Autonomous Driving: A Multi-Objective Deep Reinforcement Learning Approach.” 2019. Thesis, University of Waterloo. Accessed July 04, 2020. http://hdl.handle.net/10012/14697.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Li, Changjian. “Autonomous Driving: A Multi-Objective Deep Reinforcement Learning Approach.” 2019. Web. 04 Jul 2020.

Vancouver:

Li C. Autonomous Driving: A Multi-Objective Deep Reinforcement Learning Approach. [Internet] [Thesis]. University of Waterloo; 2019. [cited 2020 Jul 04]. Available from: http://hdl.handle.net/10012/14697.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Li C. Autonomous Driving: A Multi-Objective Deep Reinforcement Learning Approach. [Thesis]. University of Waterloo; 2019. Available from: http://hdl.handle.net/10012/14697

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Waterloo

26. Ng, Luke. Reinforcement Learning of Dynamic Collaborative Driving.

Degree: 2008, University of Waterloo

 Dynamic Collaborative Driving is the concept of decentralized multi-vehicle automated driving where vehicles form dynamic local area networks within which information is shared to build… (more)

Subjects/Keywords: autonomous robotics; mobile robots; motion control; collaborative driving; vehicle dynamics; vehicle simulation; artificial intelligence; machine learning; reinforcement learning; adaptive control

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APA (6th Edition):

Ng, L. (2008). Reinforcement Learning of Dynamic Collaborative Driving. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/3716

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Ng, Luke. “Reinforcement Learning of Dynamic Collaborative Driving.” 2008. Thesis, University of Waterloo. Accessed July 04, 2020. http://hdl.handle.net/10012/3716.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Ng, Luke. “Reinforcement Learning of Dynamic Collaborative Driving.” 2008. Web. 04 Jul 2020.

Vancouver:

Ng L. Reinforcement Learning of Dynamic Collaborative Driving. [Internet] [Thesis]. University of Waterloo; 2008. [cited 2020 Jul 04]. Available from: http://hdl.handle.net/10012/3716.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Ng L. Reinforcement Learning of Dynamic Collaborative Driving. [Thesis]. University of Waterloo; 2008. Available from: http://hdl.handle.net/10012/3716

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Waterloo

27. Taylor, Graham. Reinforcement Learning for Parameter Control of Image-Based Applications.

Degree: 2004, University of Waterloo

 The significant amount of data contained in digital images present barriers to methods of learning from the information they hold. Noise and the subjectivity of… (more)

Subjects/Keywords: Systems Design; reinforcement learning; artificial neural networks; image processing; computer vision; text detection; artificial intelligence; machine learning; parameter control; optimization; Markov decision processes; fuzzy ARTMAP

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APA (6th Edition):

Taylor, G. (2004). Reinforcement Learning for Parameter Control of Image-Based Applications. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/832

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Taylor, Graham. “Reinforcement Learning for Parameter Control of Image-Based Applications.” 2004. Thesis, University of Waterloo. Accessed July 04, 2020. http://hdl.handle.net/10012/832.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Taylor, Graham. “Reinforcement Learning for Parameter Control of Image-Based Applications.” 2004. Web. 04 Jul 2020.

Vancouver:

Taylor G. Reinforcement Learning for Parameter Control of Image-Based Applications. [Internet] [Thesis]. University of Waterloo; 2004. [cited 2020 Jul 04]. Available from: http://hdl.handle.net/10012/832.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Taylor G. Reinforcement Learning for Parameter Control of Image-Based Applications. [Thesis]. University of Waterloo; 2004. Available from: http://hdl.handle.net/10012/832

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

28. Hosseini, Seyedmohammad. Designing Intelligent Energy Management and Cost-effective Data Acquisition for Vehicular Solar Idle Reduction Systems.

Degree: 2019, University of Waterloo

 In this study, an innovative energy management system (EMS) employing the promising reinforcement learning (RL) method is proposed. The EMS intelligently administrates the power flow… (more)

Subjects/Keywords: energy management system; reinforcement learning; solar idle reduction; data acquisition; deep learning; global warming; service vehicles; auxiliary loads; hybrid vehicles

…designing EMS and have been widely studied recently [812]. Reinforcement Learning (… …Deep Reinforcement Learning (DRL) which has recently been shown to be a game… …purpose of enhancing the EMS technologies [55]. Reinforcement Learning (RL)… …Reinforcement Learning has a completely different approach for solving the problem and requires a… …and Reinforcement Learning respectively and demonstrate their basic difference. 13 Figure… 

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APA (6th Edition):

Hosseini, S. (2019). Designing Intelligent Energy Management and Cost-effective Data Acquisition for Vehicular Solar Idle Reduction Systems. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/15135

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Hosseini, Seyedmohammad. “Designing Intelligent Energy Management and Cost-effective Data Acquisition for Vehicular Solar Idle Reduction Systems.” 2019. Thesis, University of Waterloo. Accessed July 04, 2020. http://hdl.handle.net/10012/15135.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Hosseini, Seyedmohammad. “Designing Intelligent Energy Management and Cost-effective Data Acquisition for Vehicular Solar Idle Reduction Systems.” 2019. Web. 04 Jul 2020.

Vancouver:

Hosseini S. Designing Intelligent Energy Management and Cost-effective Data Acquisition for Vehicular Solar Idle Reduction Systems. [Internet] [Thesis]. University of Waterloo; 2019. [cited 2020 Jul 04]. Available from: http://hdl.handle.net/10012/15135.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Hosseini S. Designing Intelligent Energy Management and Cost-effective Data Acquisition for Vehicular Solar Idle Reduction Systems. [Thesis]. University of Waterloo; 2019. Available from: http://hdl.handle.net/10012/15135

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

29. Mooman, Abdelniser. Multi-Agent User-Centric Specialization and Collaboration for Information Retrieval.

Degree: 2012, University of Waterloo

 The amount of information on the World Wide Web (WWW) is rapidly growing in pace and topic diversity. This has made it increasingly difficult, and… (more)

Subjects/Keywords: Information retrieval; Multi-agent system; Specialized Agent; Reinforcement learning; search engines; specialized domains; personalization; IR system; user's feedback; NLP; WordNet; relevance information and feedback; Topic extractions; semantic web; ontology; clustering; data classifications; data mining

…2.3.4 Reinforcement Learning . . . . . . . . . . . . . . . . . . . . . . . . 19 Intelligent… …Specialized Agent SLA Specialized Learning Agent RL Reinforcement Learning RLA Reinforcement… …Each agent employs a Reinforcement Learning (REL) strategy to capture end user… …behaviour and interests. Reinforcement Learning allows agents to evolve their knowledge of end… …reinforcement learning (RL), and Natural Language Process (NLP), contribute to… 

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Mooman, A. (2012). Multi-Agent User-Centric Specialization and Collaboration for Information Retrieval. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/6991

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Mooman, Abdelniser. “Multi-Agent User-Centric Specialization and Collaboration for Information Retrieval.” 2012. Thesis, University of Waterloo. Accessed July 04, 2020. http://hdl.handle.net/10012/6991.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Mooman, Abdelniser. “Multi-Agent User-Centric Specialization and Collaboration for Information Retrieval.” 2012. Web. 04 Jul 2020.

Vancouver:

Mooman A. Multi-Agent User-Centric Specialization and Collaboration for Information Retrieval. [Internet] [Thesis]. University of Waterloo; 2012. [cited 2020 Jul 04]. Available from: http://hdl.handle.net/10012/6991.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Mooman A. Multi-Agent User-Centric Specialization and Collaboration for Information Retrieval. [Thesis]. University of Waterloo; 2012. Available from: http://hdl.handle.net/10012/6991

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

.