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You searched for +publisher:"Delft University of Technology" +contributor:("Oliehoek, Frans"). Showing records 1 – 5 of 5 total matches.

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Delft University of Technology

1. Samad, Azlaan Mustafa (author). Multi Agent Deep Recurrent Q-Learning for Different Traffic Demands.

Degree: 2020, Delft University of Technology

 In today’s scenario due to rapid urbanisation there has been a shift of population from rural to urban areas especially in developing countries in search… (more)

Subjects/Keywords: Deep Reinforcement Learning; Deep Q-Network; Recurrent Neural Networks

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

APA (6th Edition):

Samad, A. M. (. (2020). Multi Agent Deep Recurrent Q-Learning for Different Traffic Demands. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:84d20f53-3be7-4e85-8588-b92b962b32fe

Chicago Manual of Style (16th Edition):

Samad, Azlaan Mustafa (author). “Multi Agent Deep Recurrent Q-Learning for Different Traffic Demands.” 2020. Masters Thesis, Delft University of Technology. Accessed March 07, 2021. http://resolver.tudelft.nl/uuid:84d20f53-3be7-4e85-8588-b92b962b32fe.

MLA Handbook (7th Edition):

Samad, Azlaan Mustafa (author). “Multi Agent Deep Recurrent Q-Learning for Different Traffic Demands.” 2020. Web. 07 Mar 2021.

Vancouver:

Samad AM(. Multi Agent Deep Recurrent Q-Learning for Different Traffic Demands. [Internet] [Masters thesis]. Delft University of Technology; 2020. [cited 2021 Mar 07]. Available from: http://resolver.tudelft.nl/uuid:84d20f53-3be7-4e85-8588-b92b962b32fe.

Council of Science Editors:

Samad AM(. Multi Agent Deep Recurrent Q-Learning for Different Traffic Demands. [Masters Thesis]. Delft University of Technology; 2020. Available from: http://resolver.tudelft.nl/uuid:84d20f53-3be7-4e85-8588-b92b962b32fe


Delft University of Technology

2. van Kreveld, Ivo (author). Distributing tasks in committees: An algorithmic research in a cooperative game theory problem.

Degree: 2020, Delft University of Technology

Cooperative game theory studies multi-agent environments where agents are able to make binding agreements. A lot has been written about dividing goods or other positive… (more)

Subjects/Keywords: Game Theory; Cooperative Games; Strategyproofness; Fair Division; Task Distribution; Computational Complexity

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

APA (6th Edition):

van Kreveld, I. (. (2020). Distributing tasks in committees: An algorithmic research in a cooperative game theory problem. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:b9c9992b-e6f7-49d8-8c94-4fc7c25f7093

Chicago Manual of Style (16th Edition):

van Kreveld, Ivo (author). “Distributing tasks in committees: An algorithmic research in a cooperative game theory problem.” 2020. Masters Thesis, Delft University of Technology. Accessed March 07, 2021. http://resolver.tudelft.nl/uuid:b9c9992b-e6f7-49d8-8c94-4fc7c25f7093.

MLA Handbook (7th Edition):

van Kreveld, Ivo (author). “Distributing tasks in committees: An algorithmic research in a cooperative game theory problem.” 2020. Web. 07 Mar 2021.

Vancouver:

van Kreveld I(. Distributing tasks in committees: An algorithmic research in a cooperative game theory problem. [Internet] [Masters thesis]. Delft University of Technology; 2020. [cited 2021 Mar 07]. Available from: http://resolver.tudelft.nl/uuid:b9c9992b-e6f7-49d8-8c94-4fc7c25f7093.

Council of Science Editors:

van Kreveld I(. Distributing tasks in committees: An algorithmic research in a cooperative game theory problem. [Masters Thesis]. Delft University of Technology; 2020. Available from: http://resolver.tudelft.nl/uuid:b9c9992b-e6f7-49d8-8c94-4fc7c25f7093


Delft University of Technology

3. Hofmeister, Deniz (author). Deep Q-Network Memory Sharing: Inter-Agent Prioritised Experience Replay.

Degree: 2019, Delft University of Technology

Humans teach each other by recollecting one's own experiences and sharing them with others. The intention being that the person being taught, does not need… (more)

Subjects/Keywords: Prioritised; DQN; replay; memory; sharing

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

APA (6th Edition):

Hofmeister, D. (. (2019). Deep Q-Network Memory Sharing: Inter-Agent Prioritised Experience Replay. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:5e744262-e365-4112-b3bf-c58a908e2ac7

Chicago Manual of Style (16th Edition):

Hofmeister, Deniz (author). “Deep Q-Network Memory Sharing: Inter-Agent Prioritised Experience Replay.” 2019. Masters Thesis, Delft University of Technology. Accessed March 07, 2021. http://resolver.tudelft.nl/uuid:5e744262-e365-4112-b3bf-c58a908e2ac7.

MLA Handbook (7th Edition):

Hofmeister, Deniz (author). “Deep Q-Network Memory Sharing: Inter-Agent Prioritised Experience Replay.” 2019. Web. 07 Mar 2021.

Vancouver:

Hofmeister D(. Deep Q-Network Memory Sharing: Inter-Agent Prioritised Experience Replay. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2021 Mar 07]. Available from: http://resolver.tudelft.nl/uuid:5e744262-e365-4112-b3bf-c58a908e2ac7.

Council of Science Editors:

Hofmeister D(. Deep Q-Network Memory Sharing: Inter-Agent Prioritised Experience Replay. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:5e744262-e365-4112-b3bf-c58a908e2ac7


Delft University of Technology

4. Li, Mingxi (author). Efficient Neural Architecture Search for Language Modeling.

Degree: 2019, Delft University of Technology

Neural networks have achieved great success in many difficult learning tasks like image classification, speech recognition and natural language processing. However, neural architectures are hard… (more)

Subjects/Keywords: NAS; Deep learning; Artificial intelligence

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

APA (6th Edition):

Li, M. (. (2019). Efficient Neural Architecture Search for Language Modeling. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:aa5c948d-43c4-480d-9818-43949c67a3b5

Chicago Manual of Style (16th Edition):

Li, Mingxi (author). “Efficient Neural Architecture Search for Language Modeling.” 2019. Masters Thesis, Delft University of Technology. Accessed March 07, 2021. http://resolver.tudelft.nl/uuid:aa5c948d-43c4-480d-9818-43949c67a3b5.

MLA Handbook (7th Edition):

Li, Mingxi (author). “Efficient Neural Architecture Search for Language Modeling.” 2019. Web. 07 Mar 2021.

Vancouver:

Li M(. Efficient Neural Architecture Search for Language Modeling. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2021 Mar 07]. Available from: http://resolver.tudelft.nl/uuid:aa5c948d-43c4-480d-9818-43949c67a3b5.

Council of Science Editors:

Li M(. Efficient Neural Architecture Search for Language Modeling. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:aa5c948d-43c4-480d-9818-43949c67a3b5


Delft University of Technology

5. Grimbergen, Sherin (author). The State Space Formulation of Active Inference: Towards Brain-Inspired Robot Control.

Degree: 2019, Delft University of Technology

This thesis provides an exposition of the theory of Active Inference in a control theoretic context. Active Inference is a remarkably powerful neuroscientific theory that… (more)

Subjects/Keywords: Active Inference; Free Energy Principle; State Space Model; Brain-Inspired; Robot Control

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

APA (6th Edition):

Grimbergen, S. (. (2019). The State Space Formulation of Active Inference: Towards Brain-Inspired Robot Control. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:0f56c37c-d22b-478b-8a85-dca615a8f419

Chicago Manual of Style (16th Edition):

Grimbergen, Sherin (author). “The State Space Formulation of Active Inference: Towards Brain-Inspired Robot Control.” 2019. Masters Thesis, Delft University of Technology. Accessed March 07, 2021. http://resolver.tudelft.nl/uuid:0f56c37c-d22b-478b-8a85-dca615a8f419.

MLA Handbook (7th Edition):

Grimbergen, Sherin (author). “The State Space Formulation of Active Inference: Towards Brain-Inspired Robot Control.” 2019. Web. 07 Mar 2021.

Vancouver:

Grimbergen S(. The State Space Formulation of Active Inference: Towards Brain-Inspired Robot Control. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2021 Mar 07]. Available from: http://resolver.tudelft.nl/uuid:0f56c37c-d22b-478b-8a85-dca615a8f419.

Council of Science Editors:

Grimbergen S(. The State Space Formulation of Active Inference: Towards Brain-Inspired Robot Control. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:0f56c37c-d22b-478b-8a85-dca615a8f419

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