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You searched for subject:(reinforcement learning). Showing records 1 – 30 of 725 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 April 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 Apr 2020.

Vancouver:

Mehta N. Hierarchical structure discovery and transfer in sequential decision problems. [Internet] [Doctoral dissertation]. Oregon State University; 2011. [cited 2020 Apr 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 April 10, 2020. http://hdl.handle.net/1957/13662.

MLA Handbook (7th Edition):

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

Vancouver:

Proper S. Scaling multiagent reinforcement learning. [Internet] [Doctoral dissertation]. Oregon State University; 2009. [cited 2020 Apr 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 April 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 Apr 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 Apr 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


Delft University of Technology

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

MLA Handbook (7th Edition):

Van Diepen, M D M. “Avoiding failure states during reinforcement learning:.” 2011. Web. 10 Apr 2020.

Vancouver:

Van Diepen MDM. Avoiding failure states during reinforcement learning:. [Internet] [Masters thesis]. Delft University of Technology; 2011. [cited 2020 Apr 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


Delft University of Technology

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

MLA Handbook (7th Edition):

Van Rooijen, J C. “Learning Parameter Selection in Continuous Reinforcement Learning: Attempting to Reduce Tuning Effords:.” 2012. Web. 10 Apr 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 Apr 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


University of Illinois – Urbana-Champaign

6. 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 (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 April 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 Apr 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 Apr 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

7. 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 (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 April 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 Apr 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 Apr 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


Oregon State University

8. 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 April 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 Apr 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 Apr 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


Rutgers University

9. 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 (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 April 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 Apr 2020.

Vancouver:

Marivate VN. Improved empirical methods in reinforcement-learning evaluation. [Internet] [Doctoral dissertation]. Rutgers University; 2015. [cited 2020 Apr 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/


University of Waterloo

10. 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 April 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 Apr 2020.

Vancouver:

Gaurav A. Safety-Oriented Stability Biases for Continual Learning. [Internet] [Thesis]. University of Waterloo; 2020. [cited 2020 Apr 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


NSYSU

11. 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 (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 April 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 Apr 2020.

Vancouver:

Tseng Y. An Unified Approach to Inverse Reinforcement Learning by Oppositive Demonstrations. [Internet] [Thesis]. NSYSU; 2015. [cited 2020 Apr 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

12. 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 (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 April 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 Apr 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 Apr 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

13. 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 April 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 Apr 2020.

Vancouver:

Dick TB. Policy Gradient Reinforcement Learning Without Regret. [Internet] [Masters thesis]. University of Alberta; 2015. [cited 2020 Apr 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

14. 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 April 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 Apr 2020.

Vancouver:

White, Adam M. DEVELOPING A PREDICTIVE APPROACH TO KNOWLEDGE. [Internet] [Doctoral dissertation]. University of Alberta; 2015. [cited 2020 Apr 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

15. 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 April 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 Apr 2020.

Vancouver:

Jacobs M. Personalized anticoagulant management using reinforcement learning. [Internet] [Masters thesis]. University of Louisville; 2014. [cited 2020 Apr 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

16. 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 April 10, 2020. http://hdl.handle.net/1957/11721.

MLA Handbook (7th Edition):

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

Vancouver:

Zhang, Wei 1. Reinforcement learning for job-shop scheduling. [Internet] [Doctoral dissertation]. Oregon State University; 1996. [cited 2020 Apr 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

17. 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 April 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 Apr 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 Apr 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.

18. 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 April 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 Apr 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 Apr 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.

19. 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

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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 April 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 Apr 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 Apr 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.

20. Rodrigues, Alan de Souza. Model-Free and Model-Based Reinforcement Learning Strategies in the Acquisition of Sequential Behaviors : 系列運動の獲得におけるモデルフリーとモデルベース強化学習戦略; ケイレツ ウンドウ ノ カクトク ニオケル モデル フリー ト モデル ベース キョウカ ガクシュウ センリャク.

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):

Rodrigues, A. d. S. (n.d.). Model-Free and Model-Based Reinforcement Learning Strategies in the Acquisition of Sequential Behaviors : 系列運動の獲得におけるモデルフリーとモデルベース強化学習戦略; ケイレツ ウンドウ ノ カクトク ニオケル モデル フリー ト モデル ベース キョウカ ガクシュウ センリャク. (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/10061/4681

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):

Rodrigues, Alan de Souza. “Model-Free and Model-Based Reinforcement Learning Strategies in the Acquisition of Sequential Behaviors : 系列運動の獲得におけるモデルフリーとモデルベース強化学習戦略; ケイレツ ウンドウ ノ カクトク ニオケル モデル フリー ト モデル ベース キョウカ ガクシュウ センリャク.” Thesis, Nara Institute of Science and Technology / 奈良先端科学技術大学院大学. Accessed April 10, 2020. http://hdl.handle.net/10061/4681.

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):

Rodrigues, Alan de Souza. “Model-Free and Model-Based Reinforcement Learning Strategies in the Acquisition of Sequential Behaviors : 系列運動の獲得におけるモデルフリーとモデルベース強化学習戦略; ケイレツ ウンドウ ノ カクトク ニオケル モデル フリー ト モデル ベース キョウカ ガクシュウ センリャク.” Web. 10 Apr 2020.

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

Vancouver:

Rodrigues AdS. Model-Free and Model-Based Reinforcement Learning Strategies in the Acquisition of Sequential Behaviors : 系列運動の獲得におけるモデルフリーとモデルベース強化学習戦略; ケイレツ ウンドウ ノ カクトク ニオケル モデル フリー ト モデル ベース キョウカ ガクシュウ センリャク. [Internet] [Thesis]. Nara Institute of Science and Technology / 奈良先端科学技術大学院大学; [cited 2020 Apr 10]. Available from: http://hdl.handle.net/10061/4681.

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:

Rodrigues AdS. Model-Free and Model-Based Reinforcement Learning Strategies in the Acquisition of Sequential Behaviors : 系列運動の獲得におけるモデルフリーとモデルベース強化学習戦略; ケイレツ ウンドウ ノ カクトク ニオケル モデル フリー ト モデル ベース キョウカ ガクシュウ センリャク. [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/10061/4681

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

21. Morimura, Tetsuro. Efficient Task-independent Reinforcement Learning based on Policy Gradient : 方策勾配に基づく効率の良い課題非依存な強化学習法; ホウサク コウバイ ニ モトヅク コウリツ ノ ヨイ カダイ ヒ イゾン ナ キョウカ ガクシュウ ホウ.

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

Subjects/Keywords: Reinforcement learning

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

APA (6th Edition):

Morimura, T. (n.d.). Efficient Task-independent Reinforcement Learning based on Policy Gradient : 方策勾配に基づく効率の良い課題非依存な強化学習法; ホウサク コウバイ ニ モトヅク コウリツ ノ ヨイ カダイ ヒ イゾン ナ キョウカ ガクシュウ ホウ. (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/10061/4693

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):

Morimura, Tetsuro. “Efficient Task-independent Reinforcement Learning based on Policy Gradient : 方策勾配に基づく効率の良い課題非依存な強化学習法; ホウサク コウバイ ニ モトヅク コウリツ ノ ヨイ カダイ ヒ イゾン ナ キョウカ ガクシュウ ホウ.” Thesis, Nara Institute of Science and Technology / 奈良先端科学技術大学院大学. Accessed April 10, 2020. http://hdl.handle.net/10061/4693.

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):

Morimura, Tetsuro. “Efficient Task-independent Reinforcement Learning based on Policy Gradient : 方策勾配に基づく効率の良い課題非依存な強化学習法; ホウサク コウバイ ニ モトヅク コウリツ ノ ヨイ カダイ ヒ イゾン ナ キョウカ ガクシュウ ホウ.” Web. 10 Apr 2020.

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

Vancouver:

Morimura T. Efficient Task-independent Reinforcement Learning based on Policy Gradient : 方策勾配に基づく効率の良い課題非依存な強化学習法; ホウサク コウバイ ニ モトヅク コウリツ ノ ヨイ カダイ ヒ イゾン ナ キョウカ ガクシュウ ホウ. [Internet] [Thesis]. Nara Institute of Science and Technology / 奈良先端科学技術大学院大学; [cited 2020 Apr 10]. Available from: http://hdl.handle.net/10061/4693.

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:

Morimura T. Efficient Task-independent Reinforcement Learning based on Policy Gradient : 方策勾配に基づく効率の良い課題非依存な強化学習法; ホウサク コウバイ ニ モトヅク コウリツ ノ ヨイ カダイ ヒ イゾン ナ キョウカ ガクシュウ ホウ. [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/10061/4693

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

22. Otsuka, Makoto. Goal-Oriented Representations of the External World : A Free-Energy-Based Approach : 目的指向的な外界の表現に関する研究 : 自由エネルギーからのアプローチ; モクテキ シコウテキナ ガイカイ ノ ヒョウゲン ニ カンスル ケンキュウ : ジユウ エネルギー カラノ アプローチ.

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):

Otsuka, M. (n.d.). Goal-Oriented Representations of the External World : A Free-Energy-Based Approach : 目的指向的な外界の表現に関する研究 : 自由エネルギーからのアプローチ; モクテキ シコウテキナ ガイカイ ノ ヒョウゲン ニ カンスル ケンキュウ : ジユウ エネルギー カラノ アプローチ. (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/10061/5548

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):

Otsuka, Makoto. “Goal-Oriented Representations of the External World : A Free-Energy-Based Approach : 目的指向的な外界の表現に関する研究 : 自由エネルギーからのアプローチ; モクテキ シコウテキナ ガイカイ ノ ヒョウゲン ニ カンスル ケンキュウ : ジユウ エネルギー カラノ アプローチ.” Thesis, Nara Institute of Science and Technology / 奈良先端科学技術大学院大学. Accessed April 10, 2020. http://hdl.handle.net/10061/5548.

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):

Otsuka, Makoto. “Goal-Oriented Representations of the External World : A Free-Energy-Based Approach : 目的指向的な外界の表現に関する研究 : 自由エネルギーからのアプローチ; モクテキ シコウテキナ ガイカイ ノ ヒョウゲン ニ カンスル ケンキュウ : ジユウ エネルギー カラノ アプローチ.” Web. 10 Apr 2020.

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

Vancouver:

Otsuka M. Goal-Oriented Representations of the External World : A Free-Energy-Based Approach : 目的指向的な外界の表現に関する研究 : 自由エネルギーからのアプローチ; モクテキ シコウテキナ ガイカイ ノ ヒョウゲン ニ カンスル ケンキュウ : ジユウ エネルギー カラノ アプローチ. [Internet] [Thesis]. Nara Institute of Science and Technology / 奈良先端科学技術大学院大学; [cited 2020 Apr 10]. Available from: http://hdl.handle.net/10061/5548.

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:

Otsuka M. Goal-Oriented Representations of the External World : A Free-Energy-Based Approach : 目的指向的な外界の表現に関する研究 : 自由エネルギーからのアプローチ; モクテキ シコウテキナ ガイカイ ノ ヒョウゲン ニ カンスル ケンキュウ : ジユウ エネルギー カラノ アプローチ. [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/10061/5548

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

23. Koyanagi, Izumi. Reinforcement Learning-based Lightpath Establishment in All-Optical WDM Networks : 全光WDM網における強化学習を用いた光パス設定法; ゼンコウ WDM モウ ニ オケル キョウカ ガクシュウ オ モチイタ ヒカリ パス セッテイ ホウ.

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

Subjects/Keywords: Reinforcement learning

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

APA (6th Edition):

Koyanagi, I. (n.d.). Reinforcement Learning-based Lightpath Establishment in All-Optical WDM Networks : 全光WDM網における強化学習を用いた光パス設定法; ゼンコウ WDM モウ ニ オケル キョウカ ガクシュウ オ モチイタ ヒカリ パス セッテイ ホウ. (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/10061/5630

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):

Koyanagi, Izumi. “Reinforcement Learning-based Lightpath Establishment in All-Optical WDM Networks : 全光WDM網における強化学習を用いた光パス設定法; ゼンコウ WDM モウ ニ オケル キョウカ ガクシュウ オ モチイタ ヒカリ パス セッテイ ホウ.” Thesis, Nara Institute of Science and Technology / 奈良先端科学技術大学院大学. Accessed April 10, 2020. http://hdl.handle.net/10061/5630.

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):

Koyanagi, Izumi. “Reinforcement Learning-based Lightpath Establishment in All-Optical WDM Networks : 全光WDM網における強化学習を用いた光パス設定法; ゼンコウ WDM モウ ニ オケル キョウカ ガクシュウ オ モチイタ ヒカリ パス セッテイ ホウ.” Web. 10 Apr 2020.

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

Vancouver:

Koyanagi I. Reinforcement Learning-based Lightpath Establishment in All-Optical WDM Networks : 全光WDM網における強化学習を用いた光パス設定法; ゼンコウ WDM モウ ニ オケル キョウカ ガクシュウ オ モチイタ ヒカリ パス セッテイ ホウ. [Internet] [Thesis]. Nara Institute of Science and Technology / 奈良先端科学技術大学院大学; [cited 2020 Apr 10]. Available from: http://hdl.handle.net/10061/5630.

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:

Koyanagi I. Reinforcement Learning-based Lightpath Establishment in All-Optical WDM Networks : 全光WDM網における強化学習を用いた光パス設定法; ゼンコウ WDM モウ ニ オケル キョウカ ガクシュウ オ モチイタ ヒカリ パス セッテイ ホウ. [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/10061/5630

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

24. Rodrigues, Alan de Souza. Multiple Reinforcement Learning Action Selection Strategies in Prefrontal-Basal Ganglia and Cerebellar Networks : 強化学習理論に基づく意思決定戦略における前頭前野-大脳基底核-小脳系神経回路の計算論的機能に関する研究; キョウカ ガクシュウ リロン ニ モトズク イシ ケッテイ センリャク ニオケル ゼントウゼンヤ ダイノウ キテイ カク ショウノウ ケイ シンケイ カイロ ノ ケイサンロンテキ キノウ ニカンスル ケンキュウ.

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

Subjects/Keywords: reinforcement learning

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APA (6th Edition):

Rodrigues, A. d. S. (n.d.). Multiple Reinforcement Learning Action Selection Strategies in Prefrontal-Basal Ganglia and Cerebellar Networks : 強化学習理論に基づく意思決定戦略における前頭前野-大脳基底核-小脳系神経回路の計算論的機能に関する研究; キョウカ ガクシュウ リロン ニ モトズク イシ ケッテイ センリャク ニオケル ゼントウゼンヤ ダイノウ キテイ カク ショウノウ ケイ シンケイ カイロ ノ ケイサンロンテキ キノウ ニカンスル ケンキュウ. (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/10061/6637

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):

Rodrigues, Alan de Souza. “Multiple Reinforcement Learning Action Selection Strategies in Prefrontal-Basal Ganglia and Cerebellar Networks : 強化学習理論に基づく意思決定戦略における前頭前野-大脳基底核-小脳系神経回路の計算論的機能に関する研究; キョウカ ガクシュウ リロン ニ モトズク イシ ケッテイ センリャク ニオケル ゼントウゼンヤ ダイノウ キテイ カク ショウノウ ケイ シンケイ カイロ ノ ケイサンロンテキ キノウ ニカンスル ケンキュウ.” Thesis, Nara Institute of Science and Technology / 奈良先端科学技術大学院大学. Accessed April 10, 2020. http://hdl.handle.net/10061/6637.

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):

Rodrigues, Alan de Souza. “Multiple Reinforcement Learning Action Selection Strategies in Prefrontal-Basal Ganglia and Cerebellar Networks : 強化学習理論に基づく意思決定戦略における前頭前野-大脳基底核-小脳系神経回路の計算論的機能に関する研究; キョウカ ガクシュウ リロン ニ モトズク イシ ケッテイ センリャク ニオケル ゼントウゼンヤ ダイノウ キテイ カク ショウノウ ケイ シンケイ カイロ ノ ケイサンロンテキ キノウ ニカンスル ケンキュウ.” Web. 10 Apr 2020.

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

Vancouver:

Rodrigues AdS. Multiple Reinforcement Learning Action Selection Strategies in Prefrontal-Basal Ganglia and Cerebellar Networks : 強化学習理論に基づく意思決定戦略における前頭前野-大脳基底核-小脳系神経回路の計算論的機能に関する研究; キョウカ ガクシュウ リロン ニ モトズク イシ ケッテイ センリャク ニオケル ゼントウゼンヤ ダイノウ キテイ カク ショウノウ ケイ シンケイ カイロ ノ ケイサンロンテキ キノウ ニカンスル ケンキュウ. [Internet] [Thesis]. Nara Institute of Science and Technology / 奈良先端科学技術大学院大学; [cited 2020 Apr 10]. Available from: http://hdl.handle.net/10061/6637.

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:

Rodrigues AdS. Multiple Reinforcement Learning Action Selection Strategies in Prefrontal-Basal Ganglia and Cerebellar Networks : 強化学習理論に基づく意思決定戦略における前頭前野-大脳基底核-小脳系神経回路の計算論的機能に関する研究; キョウカ ガクシュウ リロン ニ モトズク イシ ケッテイ センリャク ニオケル ゼントウゼンヤ ダイノウ キテイ カク ショウノウ ケイ シンケイ カイロ ノ ケイサンロンテキ キノウ ニカンスル ケンキュウ. [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/10061/6637

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


University of Ottawa

25. Altamimi, Sadi. QoE-Fair Video Streaming over DASH .

Degree: 2018, University of Ottawa

 Video streaming has become, and is expected to remain, the dominant type of traffic over the Internet. With this high demand for multimedia streaming, there… (more)

Subjects/Keywords: DASH; QoE; Reinforcement Learning; Fairness

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

APA (6th Edition):

Altamimi, S. (2018). QoE-Fair Video Streaming over DASH . (Thesis). University of Ottawa. Retrieved from http://hdl.handle.net/10393/38591

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):

Altamimi, Sadi. “QoE-Fair Video Streaming over DASH .” 2018. Thesis, University of Ottawa. Accessed April 10, 2020. http://hdl.handle.net/10393/38591.

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

MLA Handbook (7th Edition):

Altamimi, Sadi. “QoE-Fair Video Streaming over DASH .” 2018. Web. 10 Apr 2020.

Vancouver:

Altamimi S. QoE-Fair Video Streaming over DASH . [Internet] [Thesis]. University of Ottawa; 2018. [cited 2020 Apr 10]. Available from: http://hdl.handle.net/10393/38591.

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

Council of Science Editors:

Altamimi S. QoE-Fair Video Streaming over DASH . [Thesis]. University of Ottawa; 2018. Available from: http://hdl.handle.net/10393/38591

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

26. Yoshizawa, Tomohiko. A Physiological Study of the Striatum Based on Reinforcement Learning Models of the Basal Ganglia : 大脳基底核の強化学習モデルに基づく線条体の生理学的研究; ダイノウ キテイカク ノ キョウカ ガクシュウ モデル ニ モトズク センジョウタイ ノ セイリガクテキ ケンキュウ.

Degree: 博士(理学), 2018, 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):

Yoshizawa, T. (2018). A Physiological Study of the Striatum Based on Reinforcement Learning Models of the Basal Ganglia : 大脳基底核の強化学習モデルに基づく線条体の生理学的研究; ダイノウ キテイカク ノ キョウカ ガクシュウ モデル ニ モトズク センジョウタイ ノ セイリガクテキ ケンキュウ. (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/10061/12494

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):

Yoshizawa, Tomohiko. “A Physiological Study of the Striatum Based on Reinforcement Learning Models of the Basal Ganglia : 大脳基底核の強化学習モデルに基づく線条体の生理学的研究; ダイノウ キテイカク ノ キョウカ ガクシュウ モデル ニ モトズク センジョウタイ ノ セイリガクテキ ケンキュウ.” 2018. Thesis, Nara Institute of Science and Technology / 奈良先端科学技術大学院大学. Accessed April 10, 2020. http://hdl.handle.net/10061/12494.

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

MLA Handbook (7th Edition):

Yoshizawa, Tomohiko. “A Physiological Study of the Striatum Based on Reinforcement Learning Models of the Basal Ganglia : 大脳基底核の強化学習モデルに基づく線条体の生理学的研究; ダイノウ キテイカク ノ キョウカ ガクシュウ モデル ニ モトズク センジョウタイ ノ セイリガクテキ ケンキュウ.” 2018. Web. 10 Apr 2020.

Vancouver:

Yoshizawa T. A Physiological Study of the Striatum Based on Reinforcement Learning Models of the Basal Ganglia : 大脳基底核の強化学習モデルに基づく線条体の生理学的研究; ダイノウ キテイカク ノ キョウカ ガクシュウ モデル ニ モトズク センジョウタイ ノ セイリガクテキ ケンキュウ. [Internet] [Thesis]. Nara Institute of Science and Technology / 奈良先端科学技術大学院大学; 2018. [cited 2020 Apr 10]. Available from: http://hdl.handle.net/10061/12494.

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

Council of Science Editors:

Yoshizawa T. A Physiological Study of the Striatum Based on Reinforcement Learning Models of the Basal Ganglia : 大脳基底核の強化学習モデルに基づく線条体の生理学的研究; ダイノウ キテイカク ノ キョウカ ガクシュウ モデル ニ モトズク センジョウタイ ノ セイリガクテキ ケンキュウ. [Thesis]. Nara Institute of Science and Technology / 奈良先端科学技術大学院大学; 2018. Available from: http://hdl.handle.net/10061/12494

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


Delft University of Technology

27. Feirstein, D.S. Reinforcement Learning of Potential Fields to achieve Limit-Cycle Walking:.

Degree: 2016, Delft University of Technology

Reinforcement learning is a powerful tool to derive controllers for systems where no models are available. Particularly policy search algorithms are suitable for complex systems,… (more)

Subjects/Keywords: reinforcement learning; limit-cycle walking

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

APA (6th Edition):

Feirstein, D. S. (2016). Reinforcement Learning of Potential Fields to achieve Limit-Cycle Walking:. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:1f33f282-fc8b-4393-9fa3-3abe7f471bb5

Chicago Manual of Style (16th Edition):

Feirstein, D S. “Reinforcement Learning of Potential Fields to achieve Limit-Cycle Walking:.” 2016. Masters Thesis, Delft University of Technology. Accessed April 10, 2020. http://resolver.tudelft.nl/uuid:1f33f282-fc8b-4393-9fa3-3abe7f471bb5.

MLA Handbook (7th Edition):

Feirstein, D S. “Reinforcement Learning of Potential Fields to achieve Limit-Cycle Walking:.” 2016. Web. 10 Apr 2020.

Vancouver:

Feirstein DS. Reinforcement Learning of Potential Fields to achieve Limit-Cycle Walking:. [Internet] [Masters thesis]. Delft University of Technology; 2016. [cited 2020 Apr 10]. Available from: http://resolver.tudelft.nl/uuid:1f33f282-fc8b-4393-9fa3-3abe7f471bb5.

Council of Science Editors:

Feirstein DS. Reinforcement Learning of Potential Fields to achieve Limit-Cycle Walking:. [Masters Thesis]. Delft University of Technology; 2016. Available from: http://resolver.tudelft.nl/uuid:1f33f282-fc8b-4393-9fa3-3abe7f471bb5


University of Michigan

28. Sorg, Jonathan Daniel. The Optimal Reward Problem: Designing Effective Reward for Bounded Agents.

Degree: PhD, Computer Science & Engineering, 2011, University of Michigan

 In the field of reinforcement learning, agent designers build agents which seek to maximize reward. In standard practice, one reward function serves two purposes. It… (more)

Subjects/Keywords: Reinforcement Learning; Computer Science; Engineering

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

APA (6th Edition):

Sorg, J. D. (2011). The Optimal Reward Problem: Designing Effective Reward for Bounded Agents. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/89705

Chicago Manual of Style (16th Edition):

Sorg, Jonathan Daniel. “The Optimal Reward Problem: Designing Effective Reward for Bounded Agents.” 2011. Doctoral Dissertation, University of Michigan. Accessed April 10, 2020. http://hdl.handle.net/2027.42/89705.

MLA Handbook (7th Edition):

Sorg, Jonathan Daniel. “The Optimal Reward Problem: Designing Effective Reward for Bounded Agents.” 2011. Web. 10 Apr 2020.

Vancouver:

Sorg JD. The Optimal Reward Problem: Designing Effective Reward for Bounded Agents. [Internet] [Doctoral dissertation]. University of Michigan; 2011. [cited 2020 Apr 10]. Available from: http://hdl.handle.net/2027.42/89705.

Council of Science Editors:

Sorg JD. The Optimal Reward Problem: Designing Effective Reward for Bounded Agents. [Doctoral Dissertation]. University of Michigan; 2011. Available from: http://hdl.handle.net/2027.42/89705


Rutgers University

29. Vroman, Monica C., 1980-. Maximum likelihood inverse reinforcement learning.

Degree: PhD, Computer Science, 2014, Rutgers University

Learning desirable behavior from a limited number of demonstrations, also known as inverse reinforcement learning, is a challenging task in machine learning. I apply maximum… (more)

Subjects/Keywords: Reinforcement learning; Reward (Psychology)

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

APA (6th Edition):

Vroman, Monica C., 1. (2014). Maximum likelihood inverse reinforcement learning. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/45557/

Chicago Manual of Style (16th Edition):

Vroman, Monica C., 1980-. “Maximum likelihood inverse reinforcement learning.” 2014. Doctoral Dissertation, Rutgers University. Accessed April 10, 2020. https://rucore.libraries.rutgers.edu/rutgers-lib/45557/.

MLA Handbook (7th Edition):

Vroman, Monica C., 1980-. “Maximum likelihood inverse reinforcement learning.” 2014. Web. 10 Apr 2020.

Vancouver:

Vroman, Monica C. 1. Maximum likelihood inverse reinforcement learning. [Internet] [Doctoral dissertation]. Rutgers University; 2014. [cited 2020 Apr 10]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/45557/.

Council of Science Editors:

Vroman, Monica C. 1. Maximum likelihood inverse reinforcement learning. [Doctoral Dissertation]. Rutgers University; 2014. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/45557/


Georgia Tech

30. Amaravati, Anvesha. Energy-Efficient circuits and system architectures to enable intelligence at the edge of the cloud.

Degree: PhD, Electrical and Computer Engineering, 2018, Georgia Tech

 Internet of Things (IoT) devices are collecting a large amount of data for video processing, monitoring health, etc. Transmitting the data from the sensor to… (more)

Subjects/Keywords: compressive sensing; reinforcement learning

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

APA (6th Edition):

Amaravati, A. (2018). Energy-Efficient circuits and system architectures to enable intelligence at the edge of the cloud. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/62240

Chicago Manual of Style (16th Edition):

Amaravati, Anvesha. “Energy-Efficient circuits and system architectures to enable intelligence at the edge of the cloud.” 2018. Doctoral Dissertation, Georgia Tech. Accessed April 10, 2020. http://hdl.handle.net/1853/62240.

MLA Handbook (7th Edition):

Amaravati, Anvesha. “Energy-Efficient circuits and system architectures to enable intelligence at the edge of the cloud.” 2018. Web. 10 Apr 2020.

Vancouver:

Amaravati A. Energy-Efficient circuits and system architectures to enable intelligence at the edge of the cloud. [Internet] [Doctoral dissertation]. Georgia Tech; 2018. [cited 2020 Apr 10]. Available from: http://hdl.handle.net/1853/62240.

Council of Science Editors:

Amaravati A. Energy-Efficient circuits and system architectures to enable intelligence at the edge of the cloud. [Doctoral Dissertation]. Georgia Tech; 2018. Available from: http://hdl.handle.net/1853/62240

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