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You searched for subject:(Q learning). Showing records 1 – 30 of 186 total matches.

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Delft University of Technology

1. Naruta, Anton (author). Continuous state and action Q-learning framework applied to quadrotor UAV control.

Degree: 2017, Delft University of Technology

 This paper describes an implementation of a reinforcement learning-based framework applied to the control of a multi-copter rotorcraft. The controller is based on continuous state… (more)

Subjects/Keywords: Reinforcement learning; Q-Learning; quadcopter; Neural Networks

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APA (6th Edition):

Naruta, A. (. (2017). Continuous state and action Q-learning framework applied to quadrotor UAV control. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:d7fb9b06-a75e-46df-b324-015f22521bf0

Chicago Manual of Style (16th Edition):

Naruta, Anton (author). “Continuous state and action Q-learning framework applied to quadrotor UAV control.” 2017. Masters Thesis, Delft University of Technology. Accessed March 07, 2021. http://resolver.tudelft.nl/uuid:d7fb9b06-a75e-46df-b324-015f22521bf0.

MLA Handbook (7th Edition):

Naruta, Anton (author). “Continuous state and action Q-learning framework applied to quadrotor UAV control.” 2017. Web. 07 Mar 2021.

Vancouver:

Naruta A(. Continuous state and action Q-learning framework applied to quadrotor UAV control. [Internet] [Masters thesis]. Delft University of Technology; 2017. [cited 2021 Mar 07]. Available from: http://resolver.tudelft.nl/uuid:d7fb9b06-a75e-46df-b324-015f22521bf0.

Council of Science Editors:

Naruta A(. Continuous state and action Q-learning framework applied to quadrotor UAV control. [Masters Thesis]. Delft University of Technology; 2017. Available from: http://resolver.tudelft.nl/uuid:d7fb9b06-a75e-46df-b324-015f22521bf0


Delft University of Technology

2. Molenkamp, D. (author). Intelligent Controller Selection for Aggressive Quadrotor Manoeuvring: A reinforcement learning approach.

Degree: 2016, Delft University of Technology

A novel intelligent controller selection method for quadrotor attitude and altitude control is presented that maintains performance in different regimes of the flight envelope. Conventional… (more)

Subjects/Keywords: reinforcement learning; q-learning; quadcopter; adaptive control

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APA (6th Edition):

Molenkamp, D. (. (2016). Intelligent Controller Selection for Aggressive Quadrotor Manoeuvring: A reinforcement learning approach. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:70dd7e02-d234-4774-9e54-94ba8d881de6

Chicago Manual of Style (16th Edition):

Molenkamp, D (author). “Intelligent Controller Selection for Aggressive Quadrotor Manoeuvring: A reinforcement learning approach.” 2016. Masters Thesis, Delft University of Technology. Accessed March 07, 2021. http://resolver.tudelft.nl/uuid:70dd7e02-d234-4774-9e54-94ba8d881de6.

MLA Handbook (7th Edition):

Molenkamp, D (author). “Intelligent Controller Selection for Aggressive Quadrotor Manoeuvring: A reinforcement learning approach.” 2016. Web. 07 Mar 2021.

Vancouver:

Molenkamp D(. Intelligent Controller Selection for Aggressive Quadrotor Manoeuvring: A reinforcement learning approach. [Internet] [Masters thesis]. Delft University of Technology; 2016. [cited 2021 Mar 07]. Available from: http://resolver.tudelft.nl/uuid:70dd7e02-d234-4774-9e54-94ba8d881de6.

Council of Science Editors:

Molenkamp D(. Intelligent Controller Selection for Aggressive Quadrotor Manoeuvring: A reinforcement learning approach. [Masters Thesis]. Delft University of Technology; 2016. Available from: http://resolver.tudelft.nl/uuid:70dd7e02-d234-4774-9e54-94ba8d881de6


University of KwaZulu-Natal

3. Waltham, Michael. Q-Cog: a Q-Learning based cognitive agent architecture for complex 3D virtual worlds.

Degree: 2017, University of KwaZulu-Natal

 Intelligent cognitive agents should be able to autonomously gather new knowledge and learn from their own experiences in order to adapt to a changing environment.… (more)

Subjects/Keywords: 3D.; Virtual worlds.; Q learning.; Virtual learning.

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APA (6th Edition):

Waltham, M. (2017). Q-Cog: a Q-Learning based cognitive agent architecture for complex 3D virtual worlds. (Thesis). University of KwaZulu-Natal. Retrieved from http://hdl.handle.net/10413/15654

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):

Waltham, Michael. “Q-Cog: a Q-Learning based cognitive agent architecture for complex 3D virtual worlds.” 2017. Thesis, University of KwaZulu-Natal. Accessed March 07, 2021. http://hdl.handle.net/10413/15654.

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

MLA Handbook (7th Edition):

Waltham, Michael. “Q-Cog: a Q-Learning based cognitive agent architecture for complex 3D virtual worlds.” 2017. Web. 07 Mar 2021.

Vancouver:

Waltham M. Q-Cog: a Q-Learning based cognitive agent architecture for complex 3D virtual worlds. [Internet] [Thesis]. University of KwaZulu-Natal; 2017. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/10413/15654.

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

Council of Science Editors:

Waltham M. Q-Cog: a Q-Learning based cognitive agent architecture for complex 3D virtual worlds. [Thesis]. University of KwaZulu-Natal; 2017. Available from: http://hdl.handle.net/10413/15654

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

4. Willim, Daniel. Developing a Self-learning Intelligent Agent in StarCraft II - Deep Reinforcement Learning with Imitation Learning .

Degree: Chalmers tekniska högskola / Institutionen för data och informationsteknik, 2019, Chalmers University of Technology

 Knowledge of machine learning is becoming more essential in many fields. This thesis explores and outlines the basics of machine learning through the complex game… (more)

Subjects/Keywords: Deep Q-Learning; Deep Q-Network; Imitation Learning; Machine Learning; PySC2; Reinforcement Learning; StarCraft II

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APA (6th Edition):

Willim, D. (2019). Developing a Self-learning Intelligent Agent in StarCraft II - Deep Reinforcement Learning with Imitation Learning . (Thesis). Chalmers University of Technology. Retrieved from http://hdl.handle.net/20.500.12380/301904

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):

Willim, Daniel. “Developing a Self-learning Intelligent Agent in StarCraft II - Deep Reinforcement Learning with Imitation Learning .” 2019. Thesis, Chalmers University of Technology. Accessed March 07, 2021. http://hdl.handle.net/20.500.12380/301904.

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

MLA Handbook (7th Edition):

Willim, Daniel. “Developing a Self-learning Intelligent Agent in StarCraft II - Deep Reinforcement Learning with Imitation Learning .” 2019. Web. 07 Mar 2021.

Vancouver:

Willim D. Developing a Self-learning Intelligent Agent in StarCraft II - Deep Reinforcement Learning with Imitation Learning . [Internet] [Thesis]. Chalmers University of Technology; 2019. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/20.500.12380/301904.

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

Council of Science Editors:

Willim D. Developing a Self-learning Intelligent Agent in StarCraft II - Deep Reinforcement Learning with Imitation Learning . [Thesis]. Chalmers University of Technology; 2019. Available from: http://hdl.handle.net/20.500.12380/301904

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

5. Manoel Leandro de Lima Júnior. Uma contribuição à solução do problema dos k-servos usando aprendizagem por reforço.

Degree: 2005, Universidade Federal do Rio Grande do Norte

 Neste trabalho é proposto um novo algoritmo online para o resolver o Problema dos k-Servos (PKS). O desempenho desta solução é comparado com o de… (more)

Subjects/Keywords: K-Servos; Aprendizado por Reforço; Q-Learning; ENGENHARIA ELETRICA; K-Servos; Reinforcement Learning; Q-Learning

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APA (6th Edition):

Júnior, M. L. d. L. (2005). Uma contribuição à solução do problema dos k-servos usando aprendizagem por reforço. (Thesis). Universidade Federal do Rio Grande do Norte. Retrieved from http://bdtd.bczm.ufrn.br/tedesimplificado//tde_busca/arquivo.php?codArquivo=629

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):

Júnior, Manoel Leandro de Lima. “Uma contribuição à solução do problema dos k-servos usando aprendizagem por reforço.” 2005. Thesis, Universidade Federal do Rio Grande do Norte. Accessed March 07, 2021. http://bdtd.bczm.ufrn.br/tedesimplificado//tde_busca/arquivo.php?codArquivo=629.

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

MLA Handbook (7th Edition):

Júnior, Manoel Leandro de Lima. “Uma contribuição à solução do problema dos k-servos usando aprendizagem por reforço.” 2005. Web. 07 Mar 2021.

Vancouver:

Júnior MLdL. Uma contribuição à solução do problema dos k-servos usando aprendizagem por reforço. [Internet] [Thesis]. Universidade Federal do Rio Grande do Norte; 2005. [cited 2021 Mar 07]. Available from: http://bdtd.bczm.ufrn.br/tedesimplificado//tde_busca/arquivo.php?codArquivo=629.

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

Council of Science Editors:

Júnior MLdL. Uma contribuição à solução do problema dos k-servos usando aprendizagem por reforço. [Thesis]. Universidade Federal do Rio Grande do Norte; 2005. Available from: http://bdtd.bczm.ufrn.br/tedesimplificado//tde_busca/arquivo.php?codArquivo=629

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


Universidade do Rio Grande do Norte

6. Silva, Lucileide Medeiros Dantas da. Proposta de arquitetura em Hardware para FPGA da técnica Qlearning de aprendizagem por reforço .

Degree: 2016, Universidade do Rio Grande do Norte

Q-learning is a off-policy reinforcement learning technique which has as main advantage the possibility of obtaining an optimal policy interacting with an unknown model environment.… (more)

Subjects/Keywords: FPGA; Q-learning; Aprendizagem por reforço; Hardware

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APA (6th Edition):

Silva, L. M. D. d. (2016). Proposta de arquitetura em Hardware para FPGA da técnica Qlearning de aprendizagem por reforço . (Masters Thesis). Universidade do Rio Grande do Norte. Retrieved from http://repositorio.ufrn.br/handle/123456789/22395

Chicago Manual of Style (16th Edition):

Silva, Lucileide Medeiros Dantas da. “Proposta de arquitetura em Hardware para FPGA da técnica Qlearning de aprendizagem por reforço .” 2016. Masters Thesis, Universidade do Rio Grande do Norte. Accessed March 07, 2021. http://repositorio.ufrn.br/handle/123456789/22395.

MLA Handbook (7th Edition):

Silva, Lucileide Medeiros Dantas da. “Proposta de arquitetura em Hardware para FPGA da técnica Qlearning de aprendizagem por reforço .” 2016. Web. 07 Mar 2021.

Vancouver:

Silva LMDd. Proposta de arquitetura em Hardware para FPGA da técnica Qlearning de aprendizagem por reforço . [Internet] [Masters thesis]. Universidade do Rio Grande do Norte; 2016. [cited 2021 Mar 07]. Available from: http://repositorio.ufrn.br/handle/123456789/22395.

Council of Science Editors:

Silva LMDd. Proposta de arquitetura em Hardware para FPGA da técnica Qlearning de aprendizagem por reforço . [Masters Thesis]. Universidade do Rio Grande do Norte; 2016. Available from: http://repositorio.ufrn.br/handle/123456789/22395


Texas A&M University

7. Redwine, Tobin Dean. A Model of Global Learning: How Students Change Through International High-Impact Experiences.

Degree: PhD, Agricultural Leadership, Education, and Communications, 2014, Texas A&M University

 Study abroad programs are important, increasing, impactful, and influential in agricultural disciplines. Research suggests that students who participate are changed. However, we do not yet… (more)

Subjects/Keywords: Global Learning; Study Abroad; Q Methodology

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APA (6th Edition):

Redwine, T. D. (2014). A Model of Global Learning: How Students Change Through International High-Impact Experiences. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/154044

Chicago Manual of Style (16th Edition):

Redwine, Tobin Dean. “A Model of Global Learning: How Students Change Through International High-Impact Experiences.” 2014. Doctoral Dissertation, Texas A&M University. Accessed March 07, 2021. http://hdl.handle.net/1969.1/154044.

MLA Handbook (7th Edition):

Redwine, Tobin Dean. “A Model of Global Learning: How Students Change Through International High-Impact Experiences.” 2014. Web. 07 Mar 2021.

Vancouver:

Redwine TD. A Model of Global Learning: How Students Change Through International High-Impact Experiences. [Internet] [Doctoral dissertation]. Texas A&M University; 2014. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/1969.1/154044.

Council of Science Editors:

Redwine TD. A Model of Global Learning: How Students Change Through International High-Impact Experiences. [Doctoral Dissertation]. Texas A&M University; 2014. Available from: http://hdl.handle.net/1969.1/154044


Brno University of Technology

8. Buchal, Petr. Hraní her pomocí neuronových sítí: Playing Games Using Neural Networks.

Degree: 2018, Brno University of Technology

 The aim of this bachelor thesis is to teach a neural network solving classic control theory problems and playing the turn-based game 2048 and several… (more)

Subjects/Keywords: Strojové učení; Zpětnovazební učení; Neuronové sítě; Q-učení; Hluboké Q-učení; Machine learning; Reinforcement learning; Neural networks; Q-learning; Deep Q-learning

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APA (6th Edition):

Buchal, P. (2018). Hraní her pomocí neuronových sítí: Playing Games Using Neural Networks. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/85237

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):

Buchal, Petr. “Hraní her pomocí neuronových sítí: Playing Games Using Neural Networks.” 2018. Thesis, Brno University of Technology. Accessed March 07, 2021. http://hdl.handle.net/11012/85237.

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

MLA Handbook (7th Edition):

Buchal, Petr. “Hraní her pomocí neuronových sítí: Playing Games Using Neural Networks.” 2018. Web. 07 Mar 2021.

Vancouver:

Buchal P. Hraní her pomocí neuronových sítí: Playing Games Using Neural Networks. [Internet] [Thesis]. Brno University of Technology; 2018. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/11012/85237.

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

Council of Science Editors:

Buchal P. Hraní her pomocí neuronových sítí: Playing Games Using Neural Networks. [Thesis]. Brno University of Technology; 2018. Available from: http://hdl.handle.net/11012/85237

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


Brno University of Technology

9. Chábek, Lukáš. Posilované učení pro hraní hry Starcraft: Reinforcement Learning for Starcraft Game Playing.

Degree: 2018, Brno University of Technology

 This work focuses on methods of machine learning for playing real-time strategy games. The thesis applies mainly methods of Q-learning based on reinforcement learning. The… (more)

Subjects/Keywords: Strojové učení; Umělá Intelience; Starcraft II; RTS; Q-Learning; Deep-Q-Learning; PySC2; Machine Learnig; Artificial Intelligence; Stracraft II; RTS; Q-Learning; Deep-Q-Learning; PySC2

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APA (6th Edition):

Chábek, L. (2018). Posilované učení pro hraní hry Starcraft: Reinforcement Learning for Starcraft Game Playing. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/85144

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):

Chábek, Lukáš. “Posilované učení pro hraní hry Starcraft: Reinforcement Learning for Starcraft Game Playing.” 2018. Thesis, Brno University of Technology. Accessed March 07, 2021. http://hdl.handle.net/11012/85144.

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

MLA Handbook (7th Edition):

Chábek, Lukáš. “Posilované učení pro hraní hry Starcraft: Reinforcement Learning for Starcraft Game Playing.” 2018. Web. 07 Mar 2021.

Vancouver:

Chábek L. Posilované učení pro hraní hry Starcraft: Reinforcement Learning for Starcraft Game Playing. [Internet] [Thesis]. Brno University of Technology; 2018. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/11012/85144.

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

Council of Science Editors:

Chábek L. Posilované učení pro hraní hry Starcraft: Reinforcement Learning for Starcraft Game Playing. [Thesis]. Brno University of Technology; 2018. Available from: http://hdl.handle.net/11012/85144

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


Princeton University

10. Parker, Nathan Francis. FUNCTIONAL CHARACTERIZATION OF STRIATAL AFFERENT PROJECTIONS IN THE CONTEXT OF REINFORCEMENT LEARNING .

Degree: PhD, 2019, Princeton University

 The ability for an animal to learn to associate a given action with its outcome and subsequently choose the action most likely to result in… (more)

Subjects/Keywords: Dopamine; Glutamate; Q learning; Reinforcement learning; Reward learning; Striatum

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APA (6th Edition):

Parker, N. F. (2019). FUNCTIONAL CHARACTERIZATION OF STRIATAL AFFERENT PROJECTIONS IN THE CONTEXT OF REINFORCEMENT LEARNING . (Doctoral Dissertation). Princeton University. Retrieved from http://arks.princeton.edu/ark:/88435/dsp01tt44pq779

Chicago Manual of Style (16th Edition):

Parker, Nathan Francis. “FUNCTIONAL CHARACTERIZATION OF STRIATAL AFFERENT PROJECTIONS IN THE CONTEXT OF REINFORCEMENT LEARNING .” 2019. Doctoral Dissertation, Princeton University. Accessed March 07, 2021. http://arks.princeton.edu/ark:/88435/dsp01tt44pq779.

MLA Handbook (7th Edition):

Parker, Nathan Francis. “FUNCTIONAL CHARACTERIZATION OF STRIATAL AFFERENT PROJECTIONS IN THE CONTEXT OF REINFORCEMENT LEARNING .” 2019. Web. 07 Mar 2021.

Vancouver:

Parker NF. FUNCTIONAL CHARACTERIZATION OF STRIATAL AFFERENT PROJECTIONS IN THE CONTEXT OF REINFORCEMENT LEARNING . [Internet] [Doctoral dissertation]. Princeton University; 2019. [cited 2021 Mar 07]. Available from: http://arks.princeton.edu/ark:/88435/dsp01tt44pq779.

Council of Science Editors:

Parker NF. FUNCTIONAL CHARACTERIZATION OF STRIATAL AFFERENT PROJECTIONS IN THE CONTEXT OF REINFORCEMENT LEARNING . [Doctoral Dissertation]. Princeton University; 2019. Available from: http://arks.princeton.edu/ark:/88435/dsp01tt44pq779


University of Minnesota

11. Tseng, Kuo-Shih. Learning in Human and Robot Search: Subgoal, Submodularity, and Sparsity.

Degree: PhD, Computer Science, 2016, University of Minnesota

 Search is an essential technology for various robotic applications and it is also central to human daily activities. Searching for targets efficiently consists of NP-hard… (more)

Subjects/Keywords: Compressed sensing; Probabilistic search; Q-learning; Sparse learning; Structure learning; Submodularity

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APA (6th Edition):

Tseng, K. (2016). Learning in Human and Robot Search: Subgoal, Submodularity, and Sparsity. (Doctoral Dissertation). University of Minnesota. Retrieved from http://hdl.handle.net/11299/183325

Chicago Manual of Style (16th Edition):

Tseng, Kuo-Shih. “Learning in Human and Robot Search: Subgoal, Submodularity, and Sparsity.” 2016. Doctoral Dissertation, University of Minnesota. Accessed March 07, 2021. http://hdl.handle.net/11299/183325.

MLA Handbook (7th Edition):

Tseng, Kuo-Shih. “Learning in Human and Robot Search: Subgoal, Submodularity, and Sparsity.” 2016. Web. 07 Mar 2021.

Vancouver:

Tseng K. Learning in Human and Robot Search: Subgoal, Submodularity, and Sparsity. [Internet] [Doctoral dissertation]. University of Minnesota; 2016. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/11299/183325.

Council of Science Editors:

Tseng K. Learning in Human and Robot Search: Subgoal, Submodularity, and Sparsity. [Doctoral Dissertation]. University of Minnesota; 2016. Available from: http://hdl.handle.net/11299/183325


Delft University of Technology

12. De Buysscher, Diego (author). Safe Curriculum Learning for Linear Systems With Unknown Dynamics in Primary Flight Control.

Degree: 2021, Delft University of Technology

Safe Curriculum Learning constitutes a collection of methods that aim at enabling Rein- forcement Learning (RL) algorithms on complex systems and tasks whilst considering the… (more)

Subjects/Keywords: Reinforcement Learning; Curriculum Learning; Safe Learning; Machine Learning; Q-Learning; flight control

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APA (6th Edition):

De Buysscher, D. (. (2021). Safe Curriculum Learning for Linear Systems With Unknown Dynamics in Primary Flight Control. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:022cdfe2-737e-44f4-8497-0159a826b9ea

Chicago Manual of Style (16th Edition):

De Buysscher, Diego (author). “Safe Curriculum Learning for Linear Systems With Unknown Dynamics in Primary Flight Control.” 2021. Masters Thesis, Delft University of Technology. Accessed March 07, 2021. http://resolver.tudelft.nl/uuid:022cdfe2-737e-44f4-8497-0159a826b9ea.

MLA Handbook (7th Edition):

De Buysscher, Diego (author). “Safe Curriculum Learning for Linear Systems With Unknown Dynamics in Primary Flight Control.” 2021. Web. 07 Mar 2021.

Vancouver:

De Buysscher D(. Safe Curriculum Learning for Linear Systems With Unknown Dynamics in Primary Flight Control. [Internet] [Masters thesis]. Delft University of Technology; 2021. [cited 2021 Mar 07]. Available from: http://resolver.tudelft.nl/uuid:022cdfe2-737e-44f4-8497-0159a826b9ea.

Council of Science Editors:

De Buysscher D(. Safe Curriculum Learning for Linear Systems With Unknown Dynamics in Primary Flight Control. [Masters Thesis]. Delft University of Technology; 2021. Available from: http://resolver.tudelft.nl/uuid:022cdfe2-737e-44f4-8497-0159a826b9ea


Brno University of Technology

13. Brychta, Adam. Posilované učení pro hraní robotického fotbalu: Reinforcement Learning for Robotic Soccer Playing.

Degree: 2020, Brno University of Technology

 The aim of this thesis is to create a reinforcement learning agent that is able to play a soccer. I'm working with the deep Q-learning(more)

Subjects/Keywords: posilované učení; posilované učení pro hraní fotbalu; Q-učení; hluboké Q-učení; dvojité hluboké Q-učení; reinforcement learning; reinforcement learning for soccer; Q-learning; deep Q-learning; double deep Q-learning

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APA (6th Edition):

Brychta, A. (2020). Posilované učení pro hraní robotického fotbalu: Reinforcement Learning for Robotic Soccer Playing. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/191537

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):

Brychta, Adam. “Posilované učení pro hraní robotického fotbalu: Reinforcement Learning for Robotic Soccer Playing.” 2020. Thesis, Brno University of Technology. Accessed March 07, 2021. http://hdl.handle.net/11012/191537.

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

MLA Handbook (7th Edition):

Brychta, Adam. “Posilované učení pro hraní robotického fotbalu: Reinforcement Learning for Robotic Soccer Playing.” 2020. Web. 07 Mar 2021.

Vancouver:

Brychta A. Posilované učení pro hraní robotického fotbalu: Reinforcement Learning for Robotic Soccer Playing. [Internet] [Thesis]. Brno University of Technology; 2020. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/11012/191537.

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

Council of Science Editors:

Brychta A. Posilované učení pro hraní robotického fotbalu: Reinforcement Learning for Robotic Soccer Playing. [Thesis]. Brno University of Technology; 2020. Available from: http://hdl.handle.net/11012/191537

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


Delft University of Technology

14. Juchli, Marc (author). Limit order placement optimization with Deep Reinforcement Learning: Learning from patterns in cryptocurrency market data.

Degree: 2018, Delft University of Technology

 For various reasons, financial institutions often make use of high-level trading strategies when buying and selling assets. Many individuals, irrespective or their level of prior… (more)

Subjects/Keywords: Reinforcement Learning; Q-Learning; Deep Q-Network; deep reinforcement learning; limit order; limit order placement; trading

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

APA (6th Edition):

Juchli, M. (. (2018). Limit order placement optimization with Deep Reinforcement Learning: Learning from patterns in cryptocurrency market data. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:e2e99579-541b-4b5a-8cbb-36ea17a4a93a

Chicago Manual of Style (16th Edition):

Juchli, Marc (author). “Limit order placement optimization with Deep Reinforcement Learning: Learning from patterns in cryptocurrency market data.” 2018. Masters Thesis, Delft University of Technology. Accessed March 07, 2021. http://resolver.tudelft.nl/uuid:e2e99579-541b-4b5a-8cbb-36ea17a4a93a.

MLA Handbook (7th Edition):

Juchli, Marc (author). “Limit order placement optimization with Deep Reinforcement Learning: Learning from patterns in cryptocurrency market data.” 2018. Web. 07 Mar 2021.

Vancouver:

Juchli M(. Limit order placement optimization with Deep Reinforcement Learning: Learning from patterns in cryptocurrency market data. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2021 Mar 07]. Available from: http://resolver.tudelft.nl/uuid:e2e99579-541b-4b5a-8cbb-36ea17a4a93a.

Council of Science Editors:

Juchli M(. Limit order placement optimization with Deep Reinforcement Learning: Learning from patterns in cryptocurrency market data. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:e2e99579-541b-4b5a-8cbb-36ea17a4a93a


Universiteit Utrecht

15. Denissen, N.P.M. Predicting App Launches on Mobile Devices Using Intelligent Agents and Machine Learning.

Degree: 2015, Universiteit Utrecht

 Data rich applications often have to load large amounts of data upon launch. The launch times for these applications, e.g. Facebook and NU.nl, can be… (more)

Subjects/Keywords: Intelligent; Agents; Machine; Learning; Mobile; Application; Prediction; Q-learning; reinforcement; MAS

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APA (6th Edition):

Denissen, N. P. M. (2015). Predicting App Launches on Mobile Devices Using Intelligent Agents and Machine Learning. (Masters Thesis). Universiteit Utrecht. Retrieved from http://dspace.library.uu.nl:8080/handle/1874/318233

Chicago Manual of Style (16th Edition):

Denissen, N P M. “Predicting App Launches on Mobile Devices Using Intelligent Agents and Machine Learning.” 2015. Masters Thesis, Universiteit Utrecht. Accessed March 07, 2021. http://dspace.library.uu.nl:8080/handle/1874/318233.

MLA Handbook (7th Edition):

Denissen, N P M. “Predicting App Launches on Mobile Devices Using Intelligent Agents and Machine Learning.” 2015. Web. 07 Mar 2021.

Vancouver:

Denissen NPM. Predicting App Launches on Mobile Devices Using Intelligent Agents and Machine Learning. [Internet] [Masters thesis]. Universiteit Utrecht; 2015. [cited 2021 Mar 07]. Available from: http://dspace.library.uu.nl:8080/handle/1874/318233.

Council of Science Editors:

Denissen NPM. Predicting App Launches on Mobile Devices Using Intelligent Agents and Machine Learning. [Masters Thesis]. Universiteit Utrecht; 2015. Available from: http://dspace.library.uu.nl:8080/handle/1874/318233


NSYSU

16. Lee, Jia-Lin. Adaptive Image-Based Visual Servoing of Robot Manipulators by Reinforcement Learning.

Degree: Master, Electrical Engineering, 2017, NSYSU

 The main objective of this thesis is to design an intelligent gain controller for a robot arm based on reinforcement learning methods. The controller is… (more)

Subjects/Keywords: Visual servoing; Robot arm; Q-learning; Reinforcement learning

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

APA (6th Edition):

Lee, J. (2017). Adaptive Image-Based Visual Servoing of Robot Manipulators by Reinforcement Learning. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0619117-151814

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):

Lee, Jia-Lin. “Adaptive Image-Based Visual Servoing of Robot Manipulators by Reinforcement Learning.” 2017. Thesis, NSYSU. Accessed March 07, 2021. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0619117-151814.

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

MLA Handbook (7th Edition):

Lee, Jia-Lin. “Adaptive Image-Based Visual Servoing of Robot Manipulators by Reinforcement Learning.” 2017. Web. 07 Mar 2021.

Vancouver:

Lee J. Adaptive Image-Based Visual Servoing of Robot Manipulators by Reinforcement Learning. [Internet] [Thesis]. NSYSU; 2017. [cited 2021 Mar 07]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0619117-151814.

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

Council of Science Editors:

Lee J. Adaptive Image-Based Visual Servoing of Robot Manipulators by Reinforcement Learning. [Thesis]. NSYSU; 2017. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0619117-151814

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


Colorado State University

17. Kumar, Anurag. Policy optimization for industrial benchmark using deep reinforcement learning.

Degree: MS(M.S.), Computer Science, 2020, Colorado State University

 Significant advancements have been made in the field of Reinforcement Learning (RL) in recent decades. Numerous novel RL environments and algorithms are mastering these problems… (more)

Subjects/Keywords: deep reinforcement learning; industrial benchmark; DDQN; q-learning; DQN

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APA (6th Edition):

Kumar, A. (2020). Policy optimization for industrial benchmark using deep reinforcement learning. (Masters Thesis). Colorado State University. Retrieved from http://hdl.handle.net/10217/212061

Chicago Manual of Style (16th Edition):

Kumar, Anurag. “Policy optimization for industrial benchmark using deep reinforcement learning.” 2020. Masters Thesis, Colorado State University. Accessed March 07, 2021. http://hdl.handle.net/10217/212061.

MLA Handbook (7th Edition):

Kumar, Anurag. “Policy optimization for industrial benchmark using deep reinforcement learning.” 2020. Web. 07 Mar 2021.

Vancouver:

Kumar A. Policy optimization for industrial benchmark using deep reinforcement learning. [Internet] [Masters thesis]. Colorado State University; 2020. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/10217/212061.

Council of Science Editors:

Kumar A. Policy optimization for industrial benchmark using deep reinforcement learning. [Masters Thesis]. Colorado State University; 2020. Available from: http://hdl.handle.net/10217/212061


Delft University of Technology

18. Siddiquee, Manan (author). Vision-Based Reinforcement Learning for the guidance of an AR Drone 2.

Degree: 2018, Delft University of Technology

 Reinforcement Learning (RL) has been applied to teach quadcopters guidance tasks. Most applications rely on position information from an absolute reference system such as Global… (more)

Subjects/Keywords: Reinforcement Learning; Computer Vision; Guidance; Navigation; Q-Learning; Drone; flight testing

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

APA (6th Edition):

Siddiquee, M. (. (2018). Vision-Based Reinforcement Learning for the guidance of an AR Drone 2. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:334e0430-17b8-4366-b8b6-0a5f8fb0367a

Chicago Manual of Style (16th Edition):

Siddiquee, Manan (author). “Vision-Based Reinforcement Learning for the guidance of an AR Drone 2.” 2018. Masters Thesis, Delft University of Technology. Accessed March 07, 2021. http://resolver.tudelft.nl/uuid:334e0430-17b8-4366-b8b6-0a5f8fb0367a.

MLA Handbook (7th Edition):

Siddiquee, Manan (author). “Vision-Based Reinforcement Learning for the guidance of an AR Drone 2.” 2018. Web. 07 Mar 2021.

Vancouver:

Siddiquee M(. Vision-Based Reinforcement Learning for the guidance of an AR Drone 2. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2021 Mar 07]. Available from: http://resolver.tudelft.nl/uuid:334e0430-17b8-4366-b8b6-0a5f8fb0367a.

Council of Science Editors:

Siddiquee M(. Vision-Based Reinforcement Learning for the guidance of an AR Drone 2. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:334e0430-17b8-4366-b8b6-0a5f8fb0367a

19. Holmberg, Erik. Developing escape strategies for copepods using Q-learning .

Degree: Chalmers tekniska högskola / Institutionen för fysik, 2019, Chalmers University of Technology

 Copepods are a type of small crustaceans with the ability to move using powerful jumps. This project seeks to develop a model for the dynamics… (more)

Subjects/Keywords: Machine learning; Fluid mechanics; Simulation; Copepods; Q-learning

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

APA (6th Edition):

Holmberg, E. (2019). Developing escape strategies for copepods using Q-learning . (Thesis). Chalmers University of Technology. Retrieved from http://hdl.handle.net/20.500.12380/300512

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):

Holmberg, Erik. “Developing escape strategies for copepods using Q-learning .” 2019. Thesis, Chalmers University of Technology. Accessed March 07, 2021. http://hdl.handle.net/20.500.12380/300512.

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

MLA Handbook (7th Edition):

Holmberg, Erik. “Developing escape strategies for copepods using Q-learning .” 2019. Web. 07 Mar 2021.

Vancouver:

Holmberg E. Developing escape strategies for copepods using Q-learning . [Internet] [Thesis]. Chalmers University of Technology; 2019. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/20.500.12380/300512.

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

Council of Science Editors:

Holmberg E. Developing escape strategies for copepods using Q-learning . [Thesis]. Chalmers University of Technology; 2019. Available from: http://hdl.handle.net/20.500.12380/300512

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


University of Cincinnati

20. Singh, Isha. Reinforcement Learning For Multiple Time Series.

Degree: MS, Engineering and Applied Science: Computer Science, 2019, University of Cincinnati

 In this thesis we have investigated reinforcement Learning for multiple time series data as a solution for finding optimal actions at each time point. The… (more)

Subjects/Keywords: Computer Science; Reinforcement Learning; Vector Autoregression; Q learning

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

APA (6th Edition):

Singh, I. (2019). Reinforcement Learning For Multiple Time Series. (Masters Thesis). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1573223551346074

Chicago Manual of Style (16th Edition):

Singh, Isha. “Reinforcement Learning For Multiple Time Series.” 2019. Masters Thesis, University of Cincinnati. Accessed March 07, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1573223551346074.

MLA Handbook (7th Edition):

Singh, Isha. “Reinforcement Learning For Multiple Time Series.” 2019. Web. 07 Mar 2021.

Vancouver:

Singh I. Reinforcement Learning For Multiple Time Series. [Internet] [Masters thesis]. University of Cincinnati; 2019. [cited 2021 Mar 07]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1573223551346074.

Council of Science Editors:

Singh I. Reinforcement Learning For Multiple Time Series. [Masters Thesis]. University of Cincinnati; 2019. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1573223551346074


University of Cincinnati

21. Dinger, Steven. Essays on Reinforcement Learning with Decision Trees and Accelerated Boosting of Partially Linear Additive Models.

Degree: PhD, Business: Business Administration, 2019, University of Cincinnati

 Reinforcement learning has become a popular research topic due to the recent successes in combining deep learning value function estimation and reinforcement learning. Because of… (more)

Subjects/Keywords: Statistics; Fitted Q-Iteration; Gradient Boosting; Online Random Forest; Q-Learning; Twin Boosting; Variable Selection

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

APA (6th Edition):

Dinger, S. (2019). Essays on Reinforcement Learning with Decision Trees and Accelerated Boosting of Partially Linear Additive Models. (Doctoral Dissertation). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1562923541849035

Chicago Manual of Style (16th Edition):

Dinger, Steven. “Essays on Reinforcement Learning with Decision Trees and Accelerated Boosting of Partially Linear Additive Models.” 2019. Doctoral Dissertation, University of Cincinnati. Accessed March 07, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1562923541849035.

MLA Handbook (7th Edition):

Dinger, Steven. “Essays on Reinforcement Learning with Decision Trees and Accelerated Boosting of Partially Linear Additive Models.” 2019. Web. 07 Mar 2021.

Vancouver:

Dinger S. Essays on Reinforcement Learning with Decision Trees and Accelerated Boosting of Partially Linear Additive Models. [Internet] [Doctoral dissertation]. University of Cincinnati; 2019. [cited 2021 Mar 07]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1562923541849035.

Council of Science Editors:

Dinger S. Essays on Reinforcement Learning with Decision Trees and Accelerated Boosting of Partially Linear Additive Models. [Doctoral Dissertation]. University of Cincinnati; 2019. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1562923541849035


Delft University of Technology

22. Bijl, H.J. (author). Guaranteed globally optimal continuous reinforcement learning.

Degree: 2012, Delft University of Technology

 Self-learning controllers offer various strong benefits over conventional controllers, the most important one being their ability to adapt to unexpected circumstances. Their application is however… (more)

Subjects/Keywords: reinforcement learning; interval analysis; self-learning controllers; proven convergence; interval Q-learning

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

APA (6th Edition):

Bijl, H. J. (. (2012). Guaranteed globally optimal continuous reinforcement learning. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:dbe531db-f69d-40dc-8dc7-c0fd20cf2e01

Chicago Manual of Style (16th Edition):

Bijl, H J (author). “Guaranteed globally optimal continuous reinforcement learning.” 2012. Masters Thesis, Delft University of Technology. Accessed March 07, 2021. http://resolver.tudelft.nl/uuid:dbe531db-f69d-40dc-8dc7-c0fd20cf2e01.

MLA Handbook (7th Edition):

Bijl, H J (author). “Guaranteed globally optimal continuous reinforcement learning.” 2012. Web. 07 Mar 2021.

Vancouver:

Bijl HJ(. Guaranteed globally optimal continuous reinforcement learning. [Internet] [Masters thesis]. Delft University of Technology; 2012. [cited 2021 Mar 07]. Available from: http://resolver.tudelft.nl/uuid:dbe531db-f69d-40dc-8dc7-c0fd20cf2e01.

Council of Science Editors:

Bijl HJ(. Guaranteed globally optimal continuous reinforcement learning. [Masters Thesis]. Delft University of Technology; 2012. Available from: http://resolver.tudelft.nl/uuid:dbe531db-f69d-40dc-8dc7-c0fd20cf2e01


University of Georgia

23. Taylor, Allen. HQ-DoG.

Degree: 2014, University of Georgia

 This thesis presents HQ-DoG, an algorithm that uses hierarchical Q-learning to learn a policy that controls a team of ten soldiers in a video game… (more)

Subjects/Keywords: Reinforcement Learning; Hierarchical Reinforcement Learning; Q-Learning; Artificial Intelligence; Games; Video Games; Domination

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

APA (6th Edition):

Taylor, A. (2014). HQ-DoG. (Thesis). University of Georgia. Retrieved from http://hdl.handle.net/10724/28433

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

Chicago Manual of Style (16th Edition):

Taylor, Allen. “HQ-DoG.” 2014. Thesis, University of Georgia. Accessed March 07, 2021. http://hdl.handle.net/10724/28433.

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

MLA Handbook (7th Edition):

Taylor, Allen. “HQ-DoG.” 2014. Web. 07 Mar 2021.

Vancouver:

Taylor A. HQ-DoG. [Internet] [Thesis]. University of Georgia; 2014. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/10724/28433.

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

Council of Science Editors:

Taylor A. HQ-DoG. [Thesis]. University of Georgia; 2014. Available from: http://hdl.handle.net/10724/28433

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


Universidade do Rio Grande do Norte

24. Santos, João Paulo Queiroz dos. Uma implementação paralela híbrida para o problema do caixeiro viajante usando algoritmos genéticos, GRASP e aprendizagem por reforço .

Degree: 2009, Universidade do Rio Grande do Norte

 The metaheuristics techiniques are known to solve optimization problems classified as NP-complete and are successful in obtaining good quality solutions. They use non-deterministic approaches to… (more)

Subjects/Keywords: Metaheurísticas GRASP; Algoritmos genéticos; Q-learning; Sistemas paralelos e distribuídos; GRASP metaheuristics; Genetic algorithm; Q-learning; Parallel and distributed systems

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

APA (6th Edition):

Santos, J. P. Q. d. (2009). Uma implementação paralela híbrida para o problema do caixeiro viajante usando algoritmos genéticos, GRASP e aprendizagem por reforço . (Masters Thesis). Universidade do Rio Grande do Norte. Retrieved from http://repositorio.ufrn.br/handle/123456789/15221

Chicago Manual of Style (16th Edition):

Santos, João Paulo Queiroz dos. “Uma implementação paralela híbrida para o problema do caixeiro viajante usando algoritmos genéticos, GRASP e aprendizagem por reforço .” 2009. Masters Thesis, Universidade do Rio Grande do Norte. Accessed March 07, 2021. http://repositorio.ufrn.br/handle/123456789/15221.

MLA Handbook (7th Edition):

Santos, João Paulo Queiroz dos. “Uma implementação paralela híbrida para o problema do caixeiro viajante usando algoritmos genéticos, GRASP e aprendizagem por reforço .” 2009. Web. 07 Mar 2021.

Vancouver:

Santos JPQd. Uma implementação paralela híbrida para o problema do caixeiro viajante usando algoritmos genéticos, GRASP e aprendizagem por reforço . [Internet] [Masters thesis]. Universidade do Rio Grande do Norte; 2009. [cited 2021 Mar 07]. Available from: http://repositorio.ufrn.br/handle/123456789/15221.

Council of Science Editors:

Santos JPQd. Uma implementação paralela híbrida para o problema do caixeiro viajante usando algoritmos genéticos, GRASP e aprendizagem por reforço . [Masters Thesis]. Universidade do Rio Grande do Norte; 2009. Available from: http://repositorio.ufrn.br/handle/123456789/15221


Universidade do Rio Grande do Norte

25. Santos, João Paulo Queiroz dos. Uma implementação paralela híbrida para o problema do caixeiro viajante usando algoritmos genéticos, GRASP e aprendizagem por reforço .

Degree: 2009, Universidade do Rio Grande do Norte

 The metaheuristics techiniques are known to solve optimization problems classified as NP-complete and are successful in obtaining good quality solutions. They use non-deterministic approaches to… (more)

Subjects/Keywords: Metaheurísticas GRASP; Algoritmos genéticos; Q-learning; Sistemas paralelos e distribuídos; GRASP metaheuristics; Genetic algorithm; Q-learning; Parallel and distributed systems

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

APA (6th Edition):

Santos, J. P. Q. d. (2009). Uma implementação paralela híbrida para o problema do caixeiro viajante usando algoritmos genéticos, GRASP e aprendizagem por reforço . (Thesis). Universidade do Rio Grande do Norte. Retrieved from http://repositorio.ufrn.br/handle/123456789/15221

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):

Santos, João Paulo Queiroz dos. “Uma implementação paralela híbrida para o problema do caixeiro viajante usando algoritmos genéticos, GRASP e aprendizagem por reforço .” 2009. Thesis, Universidade do Rio Grande do Norte. Accessed March 07, 2021. http://repositorio.ufrn.br/handle/123456789/15221.

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

MLA Handbook (7th Edition):

Santos, João Paulo Queiroz dos. “Uma implementação paralela híbrida para o problema do caixeiro viajante usando algoritmos genéticos, GRASP e aprendizagem por reforço .” 2009. Web. 07 Mar 2021.

Vancouver:

Santos JPQd. Uma implementação paralela híbrida para o problema do caixeiro viajante usando algoritmos genéticos, GRASP e aprendizagem por reforço . [Internet] [Thesis]. Universidade do Rio Grande do Norte; 2009. [cited 2021 Mar 07]. Available from: http://repositorio.ufrn.br/handle/123456789/15221.

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

Council of Science Editors:

Santos JPQd. Uma implementação paralela híbrida para o problema do caixeiro viajante usando algoritmos genéticos, GRASP e aprendizagem por reforço . [Thesis]. Universidade do Rio Grande do Norte; 2009. Available from: http://repositorio.ufrn.br/handle/123456789/15221

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


Brno University of Technology

26. Veselovský, Michal. Plánování cesty robotu pomocí posilovaného učení: Robot path planning by means of reinforcement learning.

Degree: 2019, Brno University of Technology

 This thesis is dealing with path planning for autonomous robot in enviromenment with static obstacles. Thesis includes analysis of different approaches for path planning, description… (more)

Subjects/Keywords: Plánování cesty; posilované učení; Q-učení; robot; umělá inteligence; Path planning; reinforcement learning; Q-learning; robot; artificial intelligence

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

APA (6th Edition):

Veselovský, M. (2019). Plánování cesty robotu pomocí posilovaného učení: Robot path planning by means of reinforcement learning. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/26651

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):

Veselovský, Michal. “Plánování cesty robotu pomocí posilovaného učení: Robot path planning by means of reinforcement learning.” 2019. Thesis, Brno University of Technology. Accessed March 07, 2021. http://hdl.handle.net/11012/26651.

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

MLA Handbook (7th Edition):

Veselovský, Michal. “Plánování cesty robotu pomocí posilovaného učení: Robot path planning by means of reinforcement learning.” 2019. Web. 07 Mar 2021.

Vancouver:

Veselovský M. Plánování cesty robotu pomocí posilovaného učení: Robot path planning by means of reinforcement learning. [Internet] [Thesis]. Brno University of Technology; 2019. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/11012/26651.

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

Council of Science Editors:

Veselovský M. Plánování cesty robotu pomocí posilovaného učení: Robot path planning by means of reinforcement learning. [Thesis]. Brno University of Technology; 2019. Available from: http://hdl.handle.net/11012/26651

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


Brno University of Technology

27. Ondroušek, Vít. Využití opakovaně posilovaného učení pro řízení čtyřnohého robotu: Using of Reinforcement Learning for Four Legged Robot Control.

Degree: 2014, Brno University of Technology

 The Ph.D. thesis is focused on using the reinforcement learning for four legged robot control. The main aim is to create an adaptive control system… (more)

Subjects/Keywords: kráčivý robot; kráčivá chůze; Q-učení; posilované učení; walking robot; walking gait; Q-learning; reinforcement learning

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

APA (6th Edition):

Ondroušek, V. (2014). Využití opakovaně posilovaného učení pro řízení čtyřnohého robotu: Using of Reinforcement Learning for Four Legged Robot Control. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/7788

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):

Ondroušek, Vít. “Využití opakovaně posilovaného učení pro řízení čtyřnohého robotu: Using of Reinforcement Learning for Four Legged Robot Control.” 2014. Thesis, Brno University of Technology. Accessed March 07, 2021. http://hdl.handle.net/11012/7788.

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

MLA Handbook (7th Edition):

Ondroušek, Vít. “Využití opakovaně posilovaného učení pro řízení čtyřnohého robotu: Using of Reinforcement Learning for Four Legged Robot Control.” 2014. Web. 07 Mar 2021.

Vancouver:

Ondroušek V. Využití opakovaně posilovaného učení pro řízení čtyřnohého robotu: Using of Reinforcement Learning for Four Legged Robot Control. [Internet] [Thesis]. Brno University of Technology; 2014. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/11012/7788.

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

Council of Science Editors:

Ondroušek V. Využití opakovaně posilovaného učení pro řízení čtyřnohého robotu: Using of Reinforcement Learning for Four Legged Robot Control. [Thesis]. Brno University of Technology; 2014. Available from: http://hdl.handle.net/11012/7788

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


Brno University of Technology

28. Ondroušek, Vít. Využití opakovaně posilovaného učení pro řízení čtyřnohého robotu: Using of Reinforcement Learning for Four Legged Robot Control.

Degree: 2014, Brno University of Technology

 The Ph.D. thesis is focused on using the reinforcement learning for four legged robot control. The main aim is to create an adaptive control system… (more)

Subjects/Keywords: kráčivý robot; kráčivá chůze; Q-učení; posilované učení; walking robot; walking gait; Q-learning; reinforcement learning

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Ondroušek, V. (2014). Využití opakovaně posilovaného učení pro řízení čtyřnohého robotu: Using of Reinforcement Learning for Four Legged Robot Control. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/4459

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):

Ondroušek, Vít. “Využití opakovaně posilovaného učení pro řízení čtyřnohého robotu: Using of Reinforcement Learning for Four Legged Robot Control.” 2014. Thesis, Brno University of Technology. Accessed March 07, 2021. http://hdl.handle.net/11012/4459.

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

MLA Handbook (7th Edition):

Ondroušek, Vít. “Využití opakovaně posilovaného učení pro řízení čtyřnohého robotu: Using of Reinforcement Learning for Four Legged Robot Control.” 2014. Web. 07 Mar 2021.

Vancouver:

Ondroušek V. Využití opakovaně posilovaného učení pro řízení čtyřnohého robotu: Using of Reinforcement Learning for Four Legged Robot Control. [Internet] [Thesis]. Brno University of Technology; 2014. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/11012/4459.

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

Council of Science Editors:

Ondroušek V. Využití opakovaně posilovaného učení pro řízení čtyřnohého robotu: Using of Reinforcement Learning for Four Legged Robot Control. [Thesis]. Brno University of Technology; 2014. Available from: http://hdl.handle.net/11012/4459

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


Delft University of Technology

29. Schneider, C.C.N. (author). Intelligent signalized intersection management for mixed traffic using Deep Q-Learning.

Degree: 2020, Delft University of Technology

 Signalized urban intersections are bottlenecks for traffic and cause congestion. To improve traffic signal plans, research efforts have been made to create self-adaptive traffic controllers,… (more)

Subjects/Keywords: Intelligent intersection management; traffic signal control; mixed traffic; Connected Vehicles; CV; Reinforcement Learning; Deep Q-Network; Deep Q-Learning; Traffic Simulation

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

APA (6th Edition):

Schneider, C. C. N. (. (2020). Intelligent signalized intersection management for mixed traffic using Deep Q-Learning. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:259debb3-4583-4bb1-9cd9-a8d5b88186e4

Chicago Manual of Style (16th Edition):

Schneider, C C N (author). “Intelligent signalized intersection management for mixed traffic using Deep Q-Learning.” 2020. Masters Thesis, Delft University of Technology. Accessed March 07, 2021. http://resolver.tudelft.nl/uuid:259debb3-4583-4bb1-9cd9-a8d5b88186e4.

MLA Handbook (7th Edition):

Schneider, C C N (author). “Intelligent signalized intersection management for mixed traffic using Deep Q-Learning.” 2020. Web. 07 Mar 2021.

Vancouver:

Schneider CCN(. Intelligent signalized intersection management for mixed traffic using Deep Q-Learning. [Internet] [Masters thesis]. Delft University of Technology; 2020. [cited 2021 Mar 07]. Available from: http://resolver.tudelft.nl/uuid:259debb3-4583-4bb1-9cd9-a8d5b88186e4.

Council of Science Editors:

Schneider CCN(. Intelligent signalized intersection management for mixed traffic using Deep Q-Learning. [Masters Thesis]. Delft University of Technology; 2020. Available from: http://resolver.tudelft.nl/uuid:259debb3-4583-4bb1-9cd9-a8d5b88186e4

30. Baniya, Abiral. Adaptive Interventions Treatment Modelling and Regimen Optimization Using Sequential Multiple Assignment Randomized Trials (Smart) and Q-Learning.

Degree: MS, Electrical Engineering and Computer Science, 2018, South Dakota State University

  Nowadays, pharmacological practices are focused on a single best treatment to treat a disease which sounds impractical as the same treatment may not work… (more)

Subjects/Keywords: Personalized medicine; Q-functions; Q-learning; Reinforcement Learning; SMART Design; Treatment regimen; Biomedical; Electrical and Computer Engineering

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

APA (6th Edition):

Baniya, A. (2018). Adaptive Interventions Treatment Modelling and Regimen Optimization Using Sequential Multiple Assignment Randomized Trials (Smart) and Q-Learning. (Masters Thesis). South Dakota State University. Retrieved from https://openprairie.sdstate.edu/etd/2473

Chicago Manual of Style (16th Edition):

Baniya, Abiral. “Adaptive Interventions Treatment Modelling and Regimen Optimization Using Sequential Multiple Assignment Randomized Trials (Smart) and Q-Learning.” 2018. Masters Thesis, South Dakota State University. Accessed March 07, 2021. https://openprairie.sdstate.edu/etd/2473.

MLA Handbook (7th Edition):

Baniya, Abiral. “Adaptive Interventions Treatment Modelling and Regimen Optimization Using Sequential Multiple Assignment Randomized Trials (Smart) and Q-Learning.” 2018. Web. 07 Mar 2021.

Vancouver:

Baniya A. Adaptive Interventions Treatment Modelling and Regimen Optimization Using Sequential Multiple Assignment Randomized Trials (Smart) and Q-Learning. [Internet] [Masters thesis]. South Dakota State University; 2018. [cited 2021 Mar 07]. Available from: https://openprairie.sdstate.edu/etd/2473.

Council of Science Editors:

Baniya A. Adaptive Interventions Treatment Modelling and Regimen Optimization Using Sequential Multiple Assignment Randomized Trials (Smart) and Q-Learning. [Masters Thesis]. South Dakota State University; 2018. Available from: https://openprairie.sdstate.edu/etd/2473

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