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You searched for subject:(Reinforcement learning). Showing records 1 – 30 of 1249 total matches.

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Oregon State University

1. Mehta, Neville. Hierarchical structure discovery and transfer in sequential decision problems.

Degree: PhD, Computer Science, 2011, Oregon State University

 Acting intelligently to efficiently solve sequential decision problems requires the ability to extract hierarchical structure from the underlying domain dynamics, exploit it for optimal or… (more)

Subjects/Keywords: hierarchical reinforcement learning; Reinforcement learning

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APA (6th Edition):

Mehta, N. (2011). Hierarchical structure discovery and transfer in sequential decision problems. (Doctoral Dissertation). Oregon State University. Retrieved from http://hdl.handle.net/1957/25199

Chicago Manual of Style (16th Edition):

Mehta, Neville. “Hierarchical structure discovery and transfer in sequential decision problems.” 2011. Doctoral Dissertation, Oregon State University. Accessed July 10, 2020. http://hdl.handle.net/1957/25199.

MLA Handbook (7th Edition):

Mehta, Neville. “Hierarchical structure discovery and transfer in sequential decision problems.” 2011. Web. 10 Jul 2020.

Vancouver:

Mehta N. Hierarchical structure discovery and transfer in sequential decision problems. [Internet] [Doctoral dissertation]. Oregon State University; 2011. [cited 2020 Jul 10]. Available from: http://hdl.handle.net/1957/25199.

Council of Science Editors:

Mehta N. Hierarchical structure discovery and transfer in sequential decision problems. [Doctoral Dissertation]. Oregon State University; 2011. Available from: http://hdl.handle.net/1957/25199


Oregon State University

2. Proper, Scott. Scaling multiagent reinforcement learning.

Degree: PhD, Computer Science, 2009, Oregon State University

Reinforcement learning in real-world domains suffers from three curses of dimensionality: explosions in state and action spaces, and high stochasticity or "outcome space" explosion. Multiagent… (more)

Subjects/Keywords: Reinforcement learning; Reinforcement learning

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APA (6th Edition):

Proper, S. (2009). Scaling multiagent reinforcement learning. (Doctoral Dissertation). Oregon State University. Retrieved from http://hdl.handle.net/1957/13662

Chicago Manual of Style (16th Edition):

Proper, Scott. “Scaling multiagent reinforcement learning.” 2009. Doctoral Dissertation, Oregon State University. Accessed July 10, 2020. http://hdl.handle.net/1957/13662.

MLA Handbook (7th Edition):

Proper, Scott. “Scaling multiagent reinforcement learning.” 2009. Web. 10 Jul 2020.

Vancouver:

Proper S. Scaling multiagent reinforcement learning. [Internet] [Doctoral dissertation]. Oregon State University; 2009. [cited 2020 Jul 10]. Available from: http://hdl.handle.net/1957/13662.

Council of Science Editors:

Proper S. Scaling multiagent reinforcement learning. [Doctoral Dissertation]. Oregon State University; 2009. Available from: http://hdl.handle.net/1957/13662


Oregon State University

3. Lauer, Christopher Joseph. Determining optimal timber harvest and fuel treatment on a fire-threatened landscape using approximate dynamic programming.

Degree: PhD, 2017, Oregon State University

 Forest management in the face of fire risk is a challenging problem because fire spreads across a landscape and because its occurrence is unpredictable. Additionally,… (more)

Subjects/Keywords: reinforcement learning

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APA (6th Edition):

Lauer, C. J. (2017). Determining optimal timber harvest and fuel treatment on a fire-threatened landscape using approximate dynamic programming. (Doctoral Dissertation). Oregon State University. Retrieved from http://hdl.handle.net/1957/61678

Chicago Manual of Style (16th Edition):

Lauer, Christopher Joseph. “Determining optimal timber harvest and fuel treatment on a fire-threatened landscape using approximate dynamic programming.” 2017. Doctoral Dissertation, Oregon State University. Accessed July 10, 2020. http://hdl.handle.net/1957/61678.

MLA Handbook (7th Edition):

Lauer, Christopher Joseph. “Determining optimal timber harvest and fuel treatment on a fire-threatened landscape using approximate dynamic programming.” 2017. Web. 10 Jul 2020.

Vancouver:

Lauer CJ. Determining optimal timber harvest and fuel treatment on a fire-threatened landscape using approximate dynamic programming. [Internet] [Doctoral dissertation]. Oregon State University; 2017. [cited 2020 Jul 10]. Available from: http://hdl.handle.net/1957/61678.

Council of Science Editors:

Lauer CJ. Determining optimal timber harvest and fuel treatment on a fire-threatened landscape using approximate dynamic programming. [Doctoral Dissertation]. Oregon State University; 2017. Available from: http://hdl.handle.net/1957/61678

4. Frank, Mikhail Alexander. Learning to reach and reaching to learn: a unified approach to path planning and reactive control through reinforcement learning.

Degree: 2014, Università della Svizzera italiana

 The next generation of intelligent robots will need to be able to plan reaches. Not just ballistic point to point reaches, but reaches around things… (more)

Subjects/Keywords: Reinforcement learning

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APA (6th Edition):

Frank, M. A. (2014). Learning to reach and reaching to learn: a unified approach to path planning and reactive control through reinforcement learning. (Thesis). Università della Svizzera italiana. Retrieved from http://doc.rero.ch/record/234387

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):

Frank, Mikhail Alexander. “Learning to reach and reaching to learn: a unified approach to path planning and reactive control through reinforcement learning.” 2014. Thesis, Università della Svizzera italiana. Accessed July 10, 2020. http://doc.rero.ch/record/234387.

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

MLA Handbook (7th Edition):

Frank, Mikhail Alexander. “Learning to reach and reaching to learn: a unified approach to path planning and reactive control through reinforcement learning.” 2014. Web. 10 Jul 2020.

Vancouver:

Frank MA. Learning to reach and reaching to learn: a unified approach to path planning and reactive control through reinforcement learning. [Internet] [Thesis]. Università della Svizzera italiana; 2014. [cited 2020 Jul 10]. Available from: http://doc.rero.ch/record/234387.

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

Council of Science Editors:

Frank MA. Learning to reach and reaching to learn: a unified approach to path planning and reactive control through reinforcement learning. [Thesis]. Università della Svizzera italiana; 2014. Available from: http://doc.rero.ch/record/234387

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


Delft University of Technology

5. Tian, Yuan (author). Model Free Reinforcement Learning with Stability Guarantee.

Degree: 2019, Delft University of Technology

Model-free reinforcement learning has proved to be successful in many tasks such as robotic manipulator, video games, and even stock trading. However, as the dynamics… (more)

Subjects/Keywords: Reinforcement Learning

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APA (6th Edition):

Tian, Y. (. (2019). Model Free Reinforcement Learning with Stability Guarantee. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:dde4e58f-e109-4e7f-8ecb-ed1734294e5c

Chicago Manual of Style (16th Edition):

Tian, Yuan (author). “Model Free Reinforcement Learning with Stability Guarantee.” 2019. Masters Thesis, Delft University of Technology. Accessed July 10, 2020. http://resolver.tudelft.nl/uuid:dde4e58f-e109-4e7f-8ecb-ed1734294e5c.

MLA Handbook (7th Edition):

Tian, Yuan (author). “Model Free Reinforcement Learning with Stability Guarantee.” 2019. Web. 10 Jul 2020.

Vancouver:

Tian Y(. Model Free Reinforcement Learning with Stability Guarantee. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2020 Jul 10]. Available from: http://resolver.tudelft.nl/uuid:dde4e58f-e109-4e7f-8ecb-ed1734294e5c.

Council of Science Editors:

Tian Y(. Model Free Reinforcement Learning with Stability Guarantee. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:dde4e58f-e109-4e7f-8ecb-ed1734294e5c


Delft University of Technology

6. Van Rooijen, J.C. (author). Learning Parameter Selection in Continuous Reinforcement Learning: Attempting to Reduce Tuning Effords.

Degree: 2012, Delft University of Technology

The reinforcement learning (RL) framework enables to construct controllers that try to find find an optimal control strategy in an unknown environment by trial-and-error. After… (more)

Subjects/Keywords: reinforcement learning

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

APA (6th Edition):

Van Rooijen, J. C. (. (2012). Learning Parameter Selection in Continuous Reinforcement Learning: Attempting to Reduce Tuning Effords. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:94b81bc2-aff6-457f-9b54-be5e005def38

Chicago Manual of Style (16th Edition):

Van Rooijen, J C (author). “Learning Parameter Selection in Continuous Reinforcement Learning: Attempting to Reduce Tuning Effords.” 2012. Masters Thesis, Delft University of Technology. Accessed July 10, 2020. http://resolver.tudelft.nl/uuid:94b81bc2-aff6-457f-9b54-be5e005def38.

MLA Handbook (7th Edition):

Van Rooijen, J C (author). “Learning Parameter Selection in Continuous Reinforcement Learning: Attempting to Reduce Tuning Effords.” 2012. Web. 10 Jul 2020.

Vancouver:

Van Rooijen JC(. Learning Parameter Selection in Continuous Reinforcement Learning: Attempting to Reduce Tuning Effords. [Internet] [Masters thesis]. Delft University of Technology; 2012. [cited 2020 Jul 10]. Available from: http://resolver.tudelft.nl/uuid:94b81bc2-aff6-457f-9b54-be5e005def38.

Council of Science Editors:

Van Rooijen JC(. Learning Parameter Selection in Continuous Reinforcement Learning: Attempting to Reduce Tuning Effords. [Masters Thesis]. Delft University of Technology; 2012. Available from: http://resolver.tudelft.nl/uuid:94b81bc2-aff6-457f-9b54-be5e005def38


Delft University of Technology

7. Van Diepen, M.D.M. (author). Avoiding failure states during reinforcement learning.

Degree: 2011, Delft University of Technology

The Delft Biorobotics Laboratory develops bipedal humanoid robots. One of these robots, called LEO, is designed to learn to walk using reinforcement learning. During learning,… (more)

Subjects/Keywords: reinforcement learning

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

APA (6th Edition):

Van Diepen, M. D. M. (. (2011). Avoiding failure states during reinforcement learning. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:1f03c580-9fd5-4807-87b5-d70890e05ff6

Chicago Manual of Style (16th Edition):

Van Diepen, M D M (author). “Avoiding failure states during reinforcement learning.” 2011. Masters Thesis, Delft University of Technology. Accessed July 10, 2020. http://resolver.tudelft.nl/uuid:1f03c580-9fd5-4807-87b5-d70890e05ff6.

MLA Handbook (7th Edition):

Van Diepen, M D M (author). “Avoiding failure states during reinforcement learning.” 2011. Web. 10 Jul 2020.

Vancouver:

Van Diepen MDM(. Avoiding failure states during reinforcement learning. [Internet] [Masters thesis]. Delft University of Technology; 2011. [cited 2020 Jul 10]. Available from: http://resolver.tudelft.nl/uuid:1f03c580-9fd5-4807-87b5-d70890e05ff6.

Council of Science Editors:

Van Diepen MDM(. Avoiding failure states during reinforcement learning. [Masters Thesis]. Delft University of Technology; 2011. Available from: http://resolver.tudelft.nl/uuid:1f03c580-9fd5-4807-87b5-d70890e05ff6


University of Illinois – Urbana-Champaign

8. Potok, Matthew. Safe reinforcement learning: An overview, a hybrid systems perspective, and a case study.

Degree: MS, Electrical & Computer Engr, 2018, University of Illinois – Urbana-Champaign

Reinforcement learning (RL) is a general method for agents to learn optimal control policies through exploration and experience. Due to its generality, RL can generate… (more)

Subjects/Keywords: Reinforcement Learning

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

APA (6th Edition):

Potok, M. (2018). Safe reinforcement learning: An overview, a hybrid systems perspective, and a case study. (Thesis). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/102518

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):

Potok, Matthew. “Safe reinforcement learning: An overview, a hybrid systems perspective, and a case study.” 2018. Thesis, University of Illinois – Urbana-Champaign. Accessed July 10, 2020. http://hdl.handle.net/2142/102518.

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

MLA Handbook (7th Edition):

Potok, Matthew. “Safe reinforcement learning: An overview, a hybrid systems perspective, and a case study.” 2018. Web. 10 Jul 2020.

Vancouver:

Potok M. Safe reinforcement learning: An overview, a hybrid systems perspective, and a case study. [Internet] [Thesis]. University of Illinois – Urbana-Champaign; 2018. [cited 2020 Jul 10]. Available from: http://hdl.handle.net/2142/102518.

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

Council of Science Editors:

Potok M. Safe reinforcement learning: An overview, a hybrid systems perspective, and a case study. [Thesis]. University of Illinois – Urbana-Champaign; 2018. Available from: http://hdl.handle.net/2142/102518

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


University of New South Wales

9. Ismail, Hafsa. A neural network framework for combining different task types and motivations in motivated reinforcement learning.

Degree: Engineering & Information Technology, 2014, University of New South Wales

 Combining different motivation models for different task types within artificial agents has the potential to produce agents capable of a greater range of behaviours in… (more)

Subjects/Keywords: Motivated Reinforcement Learning

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

APA (6th Edition):

Ismail, H. (2014). A neural network framework for combining different task types and motivations in motivated reinforcement learning. (Masters Thesis). University of New South Wales. Retrieved from http://handle.unsw.edu.au/1959.4/53975 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:12686/SOURCE02?view=true

Chicago Manual of Style (16th Edition):

Ismail, Hafsa. “A neural network framework for combining different task types and motivations in motivated reinforcement learning.” 2014. Masters Thesis, University of New South Wales. Accessed July 10, 2020. http://handle.unsw.edu.au/1959.4/53975 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:12686/SOURCE02?view=true.

MLA Handbook (7th Edition):

Ismail, Hafsa. “A neural network framework for combining different task types and motivations in motivated reinforcement learning.” 2014. Web. 10 Jul 2020.

Vancouver:

Ismail H. A neural network framework for combining different task types and motivations in motivated reinforcement learning. [Internet] [Masters thesis]. University of New South Wales; 2014. [cited 2020 Jul 10]. Available from: http://handle.unsw.edu.au/1959.4/53975 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:12686/SOURCE02?view=true.

Council of Science Editors:

Ismail H. A neural network framework for combining different task types and motivations in motivated reinforcement learning. [Masters Thesis]. University of New South Wales; 2014. Available from: http://handle.unsw.edu.au/1959.4/53975 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:12686/SOURCE02?view=true


Delft University of Technology

10. Keulen, Bart (author). Smart Start: A Directed and Persistent Exploration Framework for Reinforcement Learning.

Degree: 2018, Delft University of Technology

 An important problem in reinforcement learning is the exploration-exploitation dilemma. Especially for environments with sparse or misleading rewards it has proven difficult to construct a… (more)

Subjects/Keywords: Reinforcement Learning; Exploration

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APA (6th Edition):

Keulen, B. (. (2018). Smart Start: A Directed and Persistent Exploration Framework for Reinforcement Learning. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:eca20454-7905-42a1-9fb0-f72776fd5422

Chicago Manual of Style (16th Edition):

Keulen, Bart (author). “Smart Start: A Directed and Persistent Exploration Framework for Reinforcement Learning.” 2018. Masters Thesis, Delft University of Technology. Accessed July 10, 2020. http://resolver.tudelft.nl/uuid:eca20454-7905-42a1-9fb0-f72776fd5422.

MLA Handbook (7th Edition):

Keulen, Bart (author). “Smart Start: A Directed and Persistent Exploration Framework for Reinforcement Learning.” 2018. Web. 10 Jul 2020.

Vancouver:

Keulen B(. Smart Start: A Directed and Persistent Exploration Framework for Reinforcement Learning. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2020 Jul 10]. Available from: http://resolver.tudelft.nl/uuid:eca20454-7905-42a1-9fb0-f72776fd5422.

Council of Science Editors:

Keulen B(. Smart Start: A Directed and Persistent Exploration Framework for Reinforcement Learning. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:eca20454-7905-42a1-9fb0-f72776fd5422


Oregon State University

11. Wilson, Aaron (Aaron Creighton). Bayesian methods for knowledge transfer and policy search in reinforcement learning.

Degree: PhD, Computer Science, 2012, Oregon State University

 How can an agent generalize its knowledge to new circumstances? To learn effectively an agent acting in a sequential decision problem must make intelligent action… (more)

Subjects/Keywords: Machine Learning; Reinforcement learning

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

APA (6th Edition):

Wilson, A. (. C. (2012). Bayesian methods for knowledge transfer and policy search in reinforcement learning. (Doctoral Dissertation). Oregon State University. Retrieved from http://hdl.handle.net/1957/34550

Chicago Manual of Style (16th Edition):

Wilson, Aaron (Aaron Creighton). “Bayesian methods for knowledge transfer and policy search in reinforcement learning.” 2012. Doctoral Dissertation, Oregon State University. Accessed July 10, 2020. http://hdl.handle.net/1957/34550.

MLA Handbook (7th Edition):

Wilson, Aaron (Aaron Creighton). “Bayesian methods for knowledge transfer and policy search in reinforcement learning.” 2012. Web. 10 Jul 2020.

Vancouver:

Wilson A(C. Bayesian methods for knowledge transfer and policy search in reinforcement learning. [Internet] [Doctoral dissertation]. Oregon State University; 2012. [cited 2020 Jul 10]. Available from: http://hdl.handle.net/1957/34550.

Council of Science Editors:

Wilson A(C. Bayesian methods for knowledge transfer and policy search in reinforcement learning. [Doctoral Dissertation]. Oregon State University; 2012. Available from: http://hdl.handle.net/1957/34550


University of Aberdeen

12. Alexander, John W. Transfer in reinforcement learning.

Degree: PhD, 2015, University of Aberdeen

 The problem of developing skill repertoires autonomously in robotics and artificial intelligence is becoming ever more pressing. Currently, the issues of how to apply prior… (more)

Subjects/Keywords: 004; Reinforcement learning; Learning

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APA (6th Edition):

Alexander, J. W. (2015). Transfer in reinforcement learning. (Doctoral Dissertation). University of Aberdeen. Retrieved from http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?pid=227908 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.675561

Chicago Manual of Style (16th Edition):

Alexander, John W. “Transfer in reinforcement learning.” 2015. Doctoral Dissertation, University of Aberdeen. Accessed July 10, 2020. http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?pid=227908 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.675561.

MLA Handbook (7th Edition):

Alexander, John W. “Transfer in reinforcement learning.” 2015. Web. 10 Jul 2020.

Vancouver:

Alexander JW. Transfer in reinforcement learning. [Internet] [Doctoral dissertation]. University of Aberdeen; 2015. [cited 2020 Jul 10]. Available from: http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?pid=227908 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.675561.

Council of Science Editors:

Alexander JW. Transfer in reinforcement learning. [Doctoral Dissertation]. University of Aberdeen; 2015. Available from: http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?pid=227908 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.675561


Rutgers University

13. Marivate, Vukosi N. Improved empirical methods in reinforcement-learning evaluation.

Degree: PhD, Computer Science, 2015, Rutgers University

The central question addressed in this research is ”can we define evaluation methodologies that encourage reinforcement-learning (RL) algorithms to work effectively with real-life data?” First,… (more)

Subjects/Keywords: Reinforcement learning; Machine learning; Algorithms

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

APA (6th Edition):

Marivate, V. N. (2015). Improved empirical methods in reinforcement-learning evaluation. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/46389/

Chicago Manual of Style (16th Edition):

Marivate, Vukosi N. “Improved empirical methods in reinforcement-learning evaluation.” 2015. Doctoral Dissertation, Rutgers University. Accessed July 10, 2020. https://rucore.libraries.rutgers.edu/rutgers-lib/46389/.

MLA Handbook (7th Edition):

Marivate, Vukosi N. “Improved empirical methods in reinforcement-learning evaluation.” 2015. Web. 10 Jul 2020.

Vancouver:

Marivate VN. Improved empirical methods in reinforcement-learning evaluation. [Internet] [Doctoral dissertation]. Rutgers University; 2015. [cited 2020 Jul 10]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/46389/.

Council of Science Editors:

Marivate VN. Improved empirical methods in reinforcement-learning evaluation. [Doctoral Dissertation]. Rutgers University; 2015. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/46389/

14. Perundurai Rajasekaran, Siddharthan. Nonparametric Inverse Reinforcement Learning and Approximate Optimal Control with Temporal Logic Tasks.

Degree: MS, 2017, Worcester Polytechnic Institute

 "This thesis focuses on two key problems in reinforcement learning: How to design reward functions to obtain intended behaviors in autonomous systems using the learning-based… (more)

Subjects/Keywords: Learning with uncertainty; Unsupervised learning; Reinforcement Learning; Inverse Reinforcement Learning

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APA (6th Edition):

Perundurai Rajasekaran, S. (2017). Nonparametric Inverse Reinforcement Learning and Approximate Optimal Control with Temporal Logic Tasks. (Thesis). Worcester Polytechnic Institute. Retrieved from etd-083017-144531 ; https://digitalcommons.wpi.edu/etd-theses/1205

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):

Perundurai Rajasekaran, Siddharthan. “Nonparametric Inverse Reinforcement Learning and Approximate Optimal Control with Temporal Logic Tasks.” 2017. Thesis, Worcester Polytechnic Institute. Accessed July 10, 2020. etd-083017-144531 ; https://digitalcommons.wpi.edu/etd-theses/1205.

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

MLA Handbook (7th Edition):

Perundurai Rajasekaran, Siddharthan. “Nonparametric Inverse Reinforcement Learning and Approximate Optimal Control with Temporal Logic Tasks.” 2017. Web. 10 Jul 2020.

Vancouver:

Perundurai Rajasekaran S. Nonparametric Inverse Reinforcement Learning and Approximate Optimal Control with Temporal Logic Tasks. [Internet] [Thesis]. Worcester Polytechnic Institute; 2017. [cited 2020 Jul 10]. Available from: etd-083017-144531 ; https://digitalcommons.wpi.edu/etd-theses/1205.

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

Council of Science Editors:

Perundurai Rajasekaran S. Nonparametric Inverse Reinforcement Learning and Approximate Optimal Control with Temporal Logic Tasks. [Thesis]. Worcester Polytechnic Institute; 2017. Available from: etd-083017-144531 ; https://digitalcommons.wpi.edu/etd-theses/1205

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


Hong Kong University of Science and Technology

15. Wellmer, Zachary William CSE. Building and leveraging implicit models for policy gradient methods.

Degree: 2019, Hong Kong University of Science and Technology

 In this thesis, we study Policy Prediction Network and Policy Tree Network, both are deep reinforcement learning architectures offering ways to improve sample complexity and… (more)

Subjects/Keywords: Reinforcement learning ; Machine learning ; Implicit learning

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APA (6th Edition):

Wellmer, Z. W. C. (2019). Building and leveraging implicit models for policy gradient methods. (Thesis). Hong Kong University of Science and Technology. Retrieved from http://repository.ust.hk/ir/Record/1783.1-102375 ; https://doi.org/10.14711/thesis-991012757568703412 ; http://repository.ust.hk/ir/bitstream/1783.1-102375/1/th_redirect.html

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):

Wellmer, Zachary William CSE. “Building and leveraging implicit models for policy gradient methods.” 2019. Thesis, Hong Kong University of Science and Technology. Accessed July 10, 2020. http://repository.ust.hk/ir/Record/1783.1-102375 ; https://doi.org/10.14711/thesis-991012757568703412 ; http://repository.ust.hk/ir/bitstream/1783.1-102375/1/th_redirect.html.

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

MLA Handbook (7th Edition):

Wellmer, Zachary William CSE. “Building and leveraging implicit models for policy gradient methods.” 2019. Web. 10 Jul 2020.

Vancouver:

Wellmer ZWC. Building and leveraging implicit models for policy gradient methods. [Internet] [Thesis]. Hong Kong University of Science and Technology; 2019. [cited 2020 Jul 10]. Available from: http://repository.ust.hk/ir/Record/1783.1-102375 ; https://doi.org/10.14711/thesis-991012757568703412 ; http://repository.ust.hk/ir/bitstream/1783.1-102375/1/th_redirect.html.

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

Council of Science Editors:

Wellmer ZWC. Building and leveraging implicit models for policy gradient methods. [Thesis]. Hong Kong University of Science and Technology; 2019. Available from: http://repository.ust.hk/ir/Record/1783.1-102375 ; https://doi.org/10.14711/thesis-991012757568703412 ; http://repository.ust.hk/ir/bitstream/1783.1-102375/1/th_redirect.html

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


University of Waterloo

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

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 10, 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. 10 Jul 2020.

Vancouver:

Gaurav A. Safety-Oriented Stability Biases for Continual Learning. [Internet] [Thesis]. University of Waterloo; 2020. [cited 2020 Jul 10]. 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 Texas – Austin

17. Shah, Rishi Alpesh. Deep R learning for continual area sweeping.

Degree: MSin Computational Science, Engineering, and Mathematics, Computational Science, Engineering, and Mathematics, 2019, University of Texas – Austin

 In order to maintain robustness, autonomous robots need to constantly update their knowledge of the environment, which can be expensive when they are deployed in… (more)

Subjects/Keywords: Machine learning; Reinforcement learning; Robotics; Robot learning

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

APA (6th Edition):

Shah, R. A. (2019). Deep R learning for continual area sweeping. (Masters Thesis). University of Texas – Austin. Retrieved from http://dx.doi.org/10.26153/tsw/8201

Chicago Manual of Style (16th Edition):

Shah, Rishi Alpesh. “Deep R learning for continual area sweeping.” 2019. Masters Thesis, University of Texas – Austin. Accessed July 10, 2020. http://dx.doi.org/10.26153/tsw/8201.

MLA Handbook (7th Edition):

Shah, Rishi Alpesh. “Deep R learning for continual area sweeping.” 2019. Web. 10 Jul 2020.

Vancouver:

Shah RA. Deep R learning for continual area sweeping. [Internet] [Masters thesis]. University of Texas – Austin; 2019. [cited 2020 Jul 10]. Available from: http://dx.doi.org/10.26153/tsw/8201.

Council of Science Editors:

Shah RA. Deep R learning for continual area sweeping. [Masters Thesis]. University of Texas – Austin; 2019. Available from: http://dx.doi.org/10.26153/tsw/8201


NSYSU

18. Lin, Kun-da. Deep Reinforcement Learning with a Gating Network.

Degree: Master, Electrical Engineering, 2017, NSYSU

Reinforcement Learning (RL) is a good way to train the robot since it doesn't need an exact model of the environment. All need is to… (more)

Subjects/Keywords: Reinforcement Learning; Deep Reinforcement Learning; Deep Learning; Gating network; Neural network

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

APA (6th Edition):

Lin, K. (2017). Deep Reinforcement Learning with a Gating Network. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0223117-131536

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, Kun-da. “Deep Reinforcement Learning with a Gating Network.” 2017. Thesis, NSYSU. Accessed July 10, 2020. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0223117-131536.

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

MLA Handbook (7th Edition):

Lin, Kun-da. “Deep Reinforcement Learning with a Gating Network.” 2017. Web. 10 Jul 2020.

Vancouver:

Lin K. Deep Reinforcement Learning with a Gating Network. [Internet] [Thesis]. NSYSU; 2017. [cited 2020 Jul 10]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0223117-131536.

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

Council of Science Editors:

Lin K. Deep Reinforcement Learning with a Gating Network. [Thesis]. NSYSU; 2017. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0223117-131536

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


NSYSU

19. Tseng, Yi-Chia. An Unified Approach to Inverse Reinforcement Learning by Oppositive Demonstrations.

Degree: Master, Electrical Engineering, 2015, NSYSU

Reinforcement learning (RL) techniques use a reward function to correct a learning agent to solve sequential decision making problems through interactions with a dynamic environment,… (more)

Subjects/Keywords: Apprenticeship Learning; Feature weight; Inverse Reinforcement learning; Reward function; Reinforcement learning

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

APA (6th Edition):

Tseng, Y. (2015). An Unified Approach to Inverse Reinforcement Learning by Oppositive Demonstrations. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0727115-130716

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):

Tseng, Yi-Chia. “An Unified Approach to Inverse Reinforcement Learning by Oppositive Demonstrations.” 2015. Thesis, NSYSU. Accessed July 10, 2020. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0727115-130716.

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

MLA Handbook (7th Edition):

Tseng, Yi-Chia. “An Unified Approach to Inverse Reinforcement Learning by Oppositive Demonstrations.” 2015. Web. 10 Jul 2020.

Vancouver:

Tseng Y. An Unified Approach to Inverse Reinforcement Learning by Oppositive Demonstrations. [Internet] [Thesis]. NSYSU; 2015. [cited 2020 Jul 10]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0727115-130716.

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

Council of Science Editors:

Tseng Y. An Unified Approach to Inverse Reinforcement Learning by Oppositive Demonstrations. [Thesis]. NSYSU; 2015. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0727115-130716

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


NSYSU

20. Lin, Hung-shyuan. Applying The Concept of Fuzzy Logic to Inverse Reinforcement Learning.

Degree: Master, Electrical Engineering, 2015, NSYSU

 Itâs a study on Reinforcement Learning, learning interaction of agents and dynamic environment to get reward function R, and update the policy, converge learning and… (more)

Subjects/Keywords: Inverse reinforcement learning; Reward function; Fuzzy; Reinforcement learning; AdaBoost; Apprenticeship learning

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

APA (6th Edition):

Lin, H. (2015). Applying The Concept of Fuzzy Logic to Inverse Reinforcement Learning. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-1025115-185021

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, Hung-shyuan. “Applying The Concept of Fuzzy Logic to Inverse Reinforcement Learning.” 2015. Thesis, NSYSU. Accessed July 10, 2020. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-1025115-185021.

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

MLA Handbook (7th Edition):

Lin, Hung-shyuan. “Applying The Concept of Fuzzy Logic to Inverse Reinforcement Learning.” 2015. Web. 10 Jul 2020.

Vancouver:

Lin H. Applying The Concept of Fuzzy Logic to Inverse Reinforcement Learning. [Internet] [Thesis]. NSYSU; 2015. [cited 2020 Jul 10]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-1025115-185021.

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

Council of Science Editors:

Lin H. Applying The Concept of Fuzzy Logic to Inverse Reinforcement Learning. [Thesis]. NSYSU; 2015. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-1025115-185021

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


Delft University of Technology

21. van der Wijden, R. (author). Preference-driven demonstrations ranking for inverse reinforcement learning.

Degree: 2016, Delft University of Technology

New flexible teaching methods for robotics are needed to automate repetitive tasks that are currently still done by humans. For limited batch sizes, it is… (more)

Subjects/Keywords: robotics; reinforcement learning; preference learning; inverse reinforcement learning

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APA (6th Edition):

van der Wijden, R. (. (2016). Preference-driven demonstrations ranking for inverse reinforcement learning. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:4a85d32d-79da-4983-97d7-530c7bb1da98

Chicago Manual of Style (16th Edition):

van der Wijden, R (author). “Preference-driven demonstrations ranking for inverse reinforcement learning.” 2016. Masters Thesis, Delft University of Technology. Accessed July 10, 2020. http://resolver.tudelft.nl/uuid:4a85d32d-79da-4983-97d7-530c7bb1da98.

MLA Handbook (7th Edition):

van der Wijden, R (author). “Preference-driven demonstrations ranking for inverse reinforcement learning.” 2016. Web. 10 Jul 2020.

Vancouver:

van der Wijden R(. Preference-driven demonstrations ranking for inverse reinforcement learning. [Internet] [Masters thesis]. Delft University of Technology; 2016. [cited 2020 Jul 10]. Available from: http://resolver.tudelft.nl/uuid:4a85d32d-79da-4983-97d7-530c7bb1da98.

Council of Science Editors:

van der Wijden R(. Preference-driven demonstrations ranking for inverse reinforcement learning. [Masters Thesis]. Delft University of Technology; 2016. Available from: http://resolver.tudelft.nl/uuid:4a85d32d-79da-4983-97d7-530c7bb1da98


University of Waterloo

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

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 10, 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. 10 Jul 2020.

Vancouver:

Bhalla S. Deep Multi Agent Reinforcement Learning for Autonomous Driving. [Internet] [Thesis]. University of Waterloo; 2020. [cited 2020 Jul 10]. 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

23. Yunduan, Cui. Practical Model-free Reinforcement Learning in Complex Robot Systems with High Dimensional States : 高次元状態を有する複雑なロボットシステムにおける実用的なモデルフリー強化学習; コウジゲン ジョウタイ オ ユウスル フクザツナ ロボット システム ニ オケル ジツヨウテキナ モデルフリー キョウカ ガクシュウ.

Degree: 博士(工学), 2017, Nara Institute of Science and Technology / 奈良先端科学技術大学院大学

Subjects/Keywords: Reinforcement Learning

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

APA (6th Edition):

Yunduan, C. (2017). Practical Model-free Reinforcement Learning in Complex Robot Systems with High Dimensional States : 高次元状態を有する複雑なロボットシステムにおける実用的なモデルフリー強化学習; コウジゲン ジョウタイ オ ユウスル フクザツナ ロボット システム ニ オケル ジツヨウテキナ モデルフリー キョウカ ガクシュウ. (Thesis). Nara Institute of Science and Technology / 奈良先端科学技術大学院大学. Retrieved from http://hdl.handle.net/10061/12169

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):

Yunduan, Cui. “Practical Model-free Reinforcement Learning in Complex Robot Systems with High Dimensional States : 高次元状態を有する複雑なロボットシステムにおける実用的なモデルフリー強化学習; コウジゲン ジョウタイ オ ユウスル フクザツナ ロボット システム ニ オケル ジツヨウテキナ モデルフリー キョウカ ガクシュウ.” 2017. Thesis, Nara Institute of Science and Technology / 奈良先端科学技術大学院大学. Accessed July 10, 2020. http://hdl.handle.net/10061/12169.

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

MLA Handbook (7th Edition):

Yunduan, Cui. “Practical Model-free Reinforcement Learning in Complex Robot Systems with High Dimensional States : 高次元状態を有する複雑なロボットシステムにおける実用的なモデルフリー強化学習; コウジゲン ジョウタイ オ ユウスル フクザツナ ロボット システム ニ オケル ジツヨウテキナ モデルフリー キョウカ ガクシュウ.” 2017. Web. 10 Jul 2020.

Vancouver:

Yunduan C. Practical Model-free Reinforcement Learning in Complex Robot Systems with High Dimensional States : 高次元状態を有する複雑なロボットシステムにおける実用的なモデルフリー強化学習; コウジゲン ジョウタイ オ ユウスル フクザツナ ロボット システム ニ オケル ジツヨウテキナ モデルフリー キョウカ ガクシュウ. [Internet] [Thesis]. Nara Institute of Science and Technology / 奈良先端科学技術大学院大学; 2017. [cited 2020 Jul 10]. Available from: http://hdl.handle.net/10061/12169.

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

Council of Science Editors:

Yunduan C. Practical Model-free Reinforcement Learning in Complex Robot Systems with High Dimensional States : 高次元状態を有する複雑なロボットシステムにおける実用的なモデルフリー強化学習; コウジゲン ジョウタイ オ ユウスル フクザツナ ロボット システム ニ オケル ジツヨウテキナ モデルフリー キョウカ ガクシュウ. [Thesis]. Nara Institute of Science and Technology / 奈良先端科学技術大学院大学; 2017. Available from: http://hdl.handle.net/10061/12169

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


University of Alberta

24. Dick, Travis B. Policy Gradient Reinforcement Learning Without Regret.

Degree: MS, Department of Computing Science, 2015, University of Alberta

 This thesis consists of two independent projects, each contributing to a central goal of artificial intelligence research: to build computer systems that are capable of… (more)

Subjects/Keywords: Policy Gradient; Baseline; Reinforcement Learning

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

APA (6th Edition):

Dick, T. B. (2015). Policy Gradient Reinforcement Learning Without Regret. (Masters Thesis). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/df65vb663

Chicago Manual of Style (16th Edition):

Dick, Travis B. “Policy Gradient Reinforcement Learning Without Regret.” 2015. Masters Thesis, University of Alberta. Accessed July 10, 2020. https://era.library.ualberta.ca/files/df65vb663.

MLA Handbook (7th Edition):

Dick, Travis B. “Policy Gradient Reinforcement Learning Without Regret.” 2015. Web. 10 Jul 2020.

Vancouver:

Dick TB. Policy Gradient Reinforcement Learning Without Regret. [Internet] [Masters thesis]. University of Alberta; 2015. [cited 2020 Jul 10]. Available from: https://era.library.ualberta.ca/files/df65vb663.

Council of Science Editors:

Dick TB. Policy Gradient Reinforcement Learning Without Regret. [Masters Thesis]. University of Alberta; 2015. Available from: https://era.library.ualberta.ca/files/df65vb663


University of Alberta

25. White, Adam, M. DEVELOPING A PREDICTIVE APPROACH TO KNOWLEDGE.

Degree: PhD, Department of Computing Science, 2015, University of Alberta

 Understanding how an artificial agent may represent, acquire, update, and use large amounts of knowledge has long been an important research challenge in artificial intelligence.… (more)

Subjects/Keywords: Reinforcement learning; Robotics; Knowledge

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APA (6th Edition):

White, Adam, M. (2015). DEVELOPING A PREDICTIVE APPROACH TO KNOWLEDGE. (Doctoral Dissertation). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/bg257h75k

Chicago Manual of Style (16th Edition):

White, Adam, M. “DEVELOPING A PREDICTIVE APPROACH TO KNOWLEDGE.” 2015. Doctoral Dissertation, University of Alberta. Accessed July 10, 2020. https://era.library.ualberta.ca/files/bg257h75k.

MLA Handbook (7th Edition):

White, Adam, M. “DEVELOPING A PREDICTIVE APPROACH TO KNOWLEDGE.” 2015. Web. 10 Jul 2020.

Vancouver:

White, Adam M. DEVELOPING A PREDICTIVE APPROACH TO KNOWLEDGE. [Internet] [Doctoral dissertation]. University of Alberta; 2015. [cited 2020 Jul 10]. Available from: https://era.library.ualberta.ca/files/bg257h75k.

Council of Science Editors:

White, Adam M. DEVELOPING A PREDICTIVE APPROACH TO KNOWLEDGE. [Doctoral Dissertation]. University of Alberta; 2015. Available from: https://era.library.ualberta.ca/files/bg257h75k


University of Louisville

26. Jacobs, Michael. Personalized anticoagulant management using reinforcement learning.

Degree: M. Eng., 2014, University of Louisville

 Introduction: There are many problems with current state-of-the-art protocols for maintenance dosing of the oral anticoagulant agent warfarin used in clinical practice. The two key… (more)

Subjects/Keywords: Reinforcement learning; Warfarin; Drug dosing

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

APA (6th Edition):

Jacobs, M. (2014). Personalized anticoagulant management using reinforcement learning. (Masters Thesis). University of Louisville. Retrieved from 10.18297/etd/670 ; https://ir.library.louisville.edu/etd/670

Chicago Manual of Style (16th Edition):

Jacobs, Michael. “Personalized anticoagulant management using reinforcement learning.” 2014. Masters Thesis, University of Louisville. Accessed July 10, 2020. 10.18297/etd/670 ; https://ir.library.louisville.edu/etd/670.

MLA Handbook (7th Edition):

Jacobs, Michael. “Personalized anticoagulant management using reinforcement learning.” 2014. Web. 10 Jul 2020.

Vancouver:

Jacobs M. Personalized anticoagulant management using reinforcement learning. [Internet] [Masters thesis]. University of Louisville; 2014. [cited 2020 Jul 10]. Available from: 10.18297/etd/670 ; https://ir.library.louisville.edu/etd/670.

Council of Science Editors:

Jacobs M. Personalized anticoagulant management using reinforcement learning. [Masters Thesis]. University of Louisville; 2014. Available from: 10.18297/etd/670 ; https://ir.library.louisville.edu/etd/670


Oregon State University

27. Zhang, Wei, 1960-. Reinforcement learning for job-shop scheduling.

Degree: PhD, Computer Science, 1996, Oregon State University

Subjects/Keywords: Reinforcement learning

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

APA (6th Edition):

Zhang, Wei, 1. (1996). Reinforcement learning for job-shop scheduling. (Doctoral Dissertation). Oregon State University. Retrieved from http://hdl.handle.net/1957/11721

Chicago Manual of Style (16th Edition):

Zhang, Wei, 1960-. “Reinforcement learning for job-shop scheduling.” 1996. Doctoral Dissertation, Oregon State University. Accessed July 10, 2020. http://hdl.handle.net/1957/11721.

MLA Handbook (7th Edition):

Zhang, Wei, 1960-. “Reinforcement learning for job-shop scheduling.” 1996. Web. 10 Jul 2020.

Vancouver:

Zhang, Wei 1. Reinforcement learning for job-shop scheduling. [Internet] [Doctoral dissertation]. Oregon State University; 1996. [cited 2020 Jul 10]. Available from: http://hdl.handle.net/1957/11721.

Council of Science Editors:

Zhang, Wei 1. Reinforcement learning for job-shop scheduling. [Doctoral Dissertation]. Oregon State University; 1996. Available from: http://hdl.handle.net/1957/11721

28. Clark, Kendrick Cheng Go. A Reinforcement Learning Model of the Shepherding Task : 羊飼い課題の強化学習モデル; ヒツジ カイ カダイ ノ キョウカ ガクシュウ モデル.

Degree: Nara Institute of Science and Technology / 奈良先端科学技術大学院大学

Subjects/Keywords: reinforcement learning

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

APA (6th Edition):

Clark, K. C. G. (n.d.). A Reinforcement Learning Model of the Shepherding Task : 羊飼い課題の強化学習モデル; ヒツジ カイ カダイ ノ キョウカ ガクシュウ モデル. (Thesis). Nara Institute of Science and Technology / 奈良先端科学技術大学院大学. Retrieved from http://hdl.handle.net/10061/10997

Note: this citation may be lacking information needed for this citation format:
No year of publication.
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Clark, Kendrick Cheng Go. “A Reinforcement Learning Model of the Shepherding Task : 羊飼い課題の強化学習モデル; ヒツジ カイ カダイ ノ キョウカ ガクシュウ モデル.” Thesis, Nara Institute of Science and Technology / 奈良先端科学技術大学院大学. Accessed July 10, 2020. http://hdl.handle.net/10061/10997.

Note: this citation may be lacking information needed for this citation format:
No year of publication.
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Clark, Kendrick Cheng Go. “A Reinforcement Learning Model of the Shepherding Task : 羊飼い課題の強化学習モデル; ヒツジ カイ カダイ ノ キョウカ ガクシュウ モデル.” Web. 10 Jul 2020.

Note: this citation may be lacking information needed for this citation format:
No year of publication.

Vancouver:

Clark KCG. A Reinforcement Learning Model of the Shepherding Task : 羊飼い課題の強化学習モデル; ヒツジ カイ カダイ ノ キョウカ ガクシュウ モデル. [Internet] [Thesis]. Nara Institute of Science and Technology / 奈良先端科学技術大学院大学; [cited 2020 Jul 10]. Available from: http://hdl.handle.net/10061/10997.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
No year of publication.

Council of Science Editors:

Clark KCG. A Reinforcement Learning Model of the Shepherding Task : 羊飼い課題の強化学習モデル; ヒツジ カイ カダイ ノ キョウカ ガクシュウ モデル. [Thesis]. Nara Institute of Science and Technology / 奈良先端科学技術大学院大学; Available from: http://hdl.handle.net/10061/10997

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
No year of publication.

29. Mauricio Alexandre Parente Burdelis. Temporal Difference Approach in Linearly Solvable Markov Decision Processes : 線形可解マルコフ決定過程における受動的ダイナミクスのモデリングと推定; センケイ カカイ マルコフ ケッテイ カテイ ニ オケル ジュドウテキ ダイナミクス ノ モデリング ト スイテイ.

Degree: 博士(工学), Nara Institute of Science and Technology / 奈良先端科学技術大学院大学

Subjects/Keywords: Reinforcement learning

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

APA (6th Edition):

Burdelis, M. A. P. (n.d.). Temporal Difference Approach in Linearly Solvable Markov Decision Processes : 線形可解マルコフ決定過程における受動的ダイナミクスのモデリングと推定; センケイ カカイ マルコフ ケッテイ カテイ ニ オケル ジュドウテキ ダイナミクス ノ モデリング ト スイテイ. (Thesis). Nara Institute of Science and Technology / 奈良先端科学技術大学院大学. Retrieved from http://hdl.handle.net/10061/9189

Note: this citation may be lacking information needed for this citation format:
No year of publication.
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Burdelis, Mauricio Alexandre Parente. “Temporal Difference Approach in Linearly Solvable Markov Decision Processes : 線形可解マルコフ決定過程における受動的ダイナミクスのモデリングと推定; センケイ カカイ マルコフ ケッテイ カテイ ニ オケル ジュドウテキ ダイナミクス ノ モデリング ト スイテイ.” Thesis, Nara Institute of Science and Technology / 奈良先端科学技術大学院大学. Accessed July 10, 2020. http://hdl.handle.net/10061/9189.

Note: this citation may be lacking information needed for this citation format:
No year of publication.
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Burdelis, Mauricio Alexandre Parente. “Temporal Difference Approach in Linearly Solvable Markov Decision Processes : 線形可解マルコフ決定過程における受動的ダイナミクスのモデリングと推定; センケイ カカイ マルコフ ケッテイ カテイ ニ オケル ジュドウテキ ダイナミクス ノ モデリング ト スイテイ.” Web. 10 Jul 2020.

Note: this citation may be lacking information needed for this citation format:
No year of publication.

Vancouver:

Burdelis MAP. Temporal Difference Approach in Linearly Solvable Markov Decision Processes : 線形可解マルコフ決定過程における受動的ダイナミクスのモデリングと推定; センケイ カカイ マルコフ ケッテイ カテイ ニ オケル ジュドウテキ ダイナミクス ノ モデリング ト スイテイ. [Internet] [Thesis]. Nara Institute of Science and Technology / 奈良先端科学技術大学院大学; [cited 2020 Jul 10]. Available from: http://hdl.handle.net/10061/9189.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
No year of publication.

Council of Science Editors:

Burdelis MAP. Temporal Difference Approach in Linearly Solvable Markov Decision Processes : 線形可解マルコフ決定過程における受動的ダイナミクスのモデリングと推定; センケイ カカイ マルコフ ケッテイ カテイ ニ オケル ジュドウテキ ダイナミクス ノ モデリング ト スイテイ. [Thesis]. Nara Institute of Science and Technology / 奈良先端科学技術大学院大学; Available from: http://hdl.handle.net/10061/9189

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
No year of publication.

30. 森本, 淳. Hierarchical Decomposition and Min-max Strategy for Fast and Robust Reinforcement Learning in the Real Environment : 階層分割とMin-max戦略による実環境での高速かつロバストな強化学習; カイソウ ブンカツ ト Min-max センリャク ニヨル ジツカンキョウ デノ コウソク カツ ロバストナ キョウカ ガクシュウ.

Degree: Nara Institute of Science and Technology / 奈良先端科学技術大学院大学

Subjects/Keywords: reinforcement learning

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

森本, . (n.d.). Hierarchical Decomposition and Min-max Strategy for Fast and Robust Reinforcement Learning in the Real Environment : 階層分割とMin-max戦略による実環境での高速かつロバストな強化学習; カイソウ ブンカツ ト Min-max センリャク ニヨル ジツカンキョウ デノ コウソク カツ ロバストナ キョウカ ガクシュウ. (Thesis). Nara Institute of Science and Technology / 奈良先端科学技術大学院大学. Retrieved from http://hdl.handle.net/10061/2966

Note: this citation may be lacking information needed for this citation format:
No year of publication.
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

森本, 淳. “Hierarchical Decomposition and Min-max Strategy for Fast and Robust Reinforcement Learning in the Real Environment : 階層分割とMin-max戦略による実環境での高速かつロバストな強化学習; カイソウ ブンカツ ト Min-max センリャク ニヨル ジツカンキョウ デノ コウソク カツ ロバストナ キョウカ ガクシュウ.” Thesis, Nara Institute of Science and Technology / 奈良先端科学技術大学院大学. Accessed July 10, 2020. http://hdl.handle.net/10061/2966.

Note: this citation may be lacking information needed for this citation format:
No year of publication.
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

森本, 淳. “Hierarchical Decomposition and Min-max Strategy for Fast and Robust Reinforcement Learning in the Real Environment : 階層分割とMin-max戦略による実環境での高速かつロバストな強化学習; カイソウ ブンカツ ト Min-max センリャク ニヨル ジツカンキョウ デノ コウソク カツ ロバストナ キョウカ ガクシュウ.” Web. 10 Jul 2020.

Note: this citation may be lacking information needed for this citation format:
No year of publication.

Vancouver:

森本 . Hierarchical Decomposition and Min-max Strategy for Fast and Robust Reinforcement Learning in the Real Environment : 階層分割とMin-max戦略による実環境での高速かつロバストな強化学習; カイソウ ブンカツ ト Min-max センリャク ニヨル ジツカンキョウ デノ コウソク カツ ロバストナ キョウカ ガクシュウ. [Internet] [Thesis]. Nara Institute of Science and Technology / 奈良先端科学技術大学院大学; [cited 2020 Jul 10]. Available from: http://hdl.handle.net/10061/2966.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
No year of publication.

Council of Science Editors:

森本 . Hierarchical Decomposition and Min-max Strategy for Fast and Robust Reinforcement Learning in the Real Environment : 階層分割とMin-max戦略による実環境での高速かつロバストな強化学習; カイソウ ブンカツ ト Min-max センリャク ニヨル ジツカンキョウ デノ コウソク カツ ロバストナ キョウカ ガクシュウ. [Thesis]. Nara Institute of Science and Technology / 奈良先端科学技術大学院大学; Available from: http://hdl.handle.net/10061/2966

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
No year of publication.

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