Exploration and value function factorisation in single and multi-agent reinforcement learning

Exploration and value function factorisation in single and multi-agent reinforcement learning

<p>The ability to learn from data is crucial in developing satisfactory solutions to many complex problems. In particular, in the design of intelligent agents that exist and interact with a complex environment in the pursuit of some goal. In this thesis we investigate some bottlenecks that can...

Mô tả đầy đủ

Chi tiết về thư mục
Tác giả chính:	Rashid, T
Tác giả khác:	Whiteson, S
Định dạng:	Luận văn
Ngôn ngữ:	English
Được phát hành:	2021
Những chủ đề:	Reinforcement learning

Những quyển sách tương tự

Monotonic value function factorisation for deep multi-agent reinforcement learning
Bằng: Rashid, T, et al.
Được phát hành: (2020)

QMIX: Monotonic value function factorisation for deep multi-agent reinforcement learning
Bằng: Rashid, T, et al.
Được phát hành: (2018)

Weighted QMIX: Expanding monotonic value function factorisation for deep multi−agent reinforcement learning
Bằng: Rashid, T, et al.
Được phát hành: (2020)

Rethinking Exploration and Experience Exploitation in Value-Based Multi-Agent Reinforcement Learning
Bằng: Anatolii Borzilov, et al.
Được phát hành: (2025-01-01)

Reinforcement Learning with Value Function Decomposition for Hierarchical Multi-Agent Consensus Control
Bằng: Xiaoxia Zhu
Được phát hành: (2024-09-01)

Applications of Multi-Agent Deep Reinforcement Learning: Models and Algorithms
Bằng: Abdikarim Mohamed Ibrahim, et al.
Được phát hành: (2021-11-01)

Coordination and communication in deep multi-agent reinforcement learning
Bằng: Schroeder de Witt, CA
Được phát hành: (2021)

The Important Role of Global State for Multi-Agent Reinforcement Learning
Bằng: Shuailong Li, et al.
Được phát hành: (2021-12-01)

Investigation of independent reinforcement learning algorithms in multi-agent environments
Bằng: Ken Ming Lee, et al.
Được phát hành: (2022-09-01)

Knowledge- and Model-Driven Deep Reinforcement Learning for Efficient Federated Edge Learning: Single- and Multi-Agent Frameworks
Bằng: Yangchen Li, et al.
Được phát hành: (2025-01-01)

Multi-agent reinforcement learning for traffic congestion on one-way multi-lane highways
Bằng: Nguyen-Tuan-Thanh Le
Được phát hành: (2023-07-01)

WRFMR: A Multi-Agent Reinforcement Learning Method for Cooperative Tasks
Bằng: Hui Liu, et al.
Được phát hành: (2020-01-01)

Noise-Regularized Advantage Value for Multi-Agent Reinforcement Learning
Bằng: Siying Wang, et al.
Được phát hành: (2022-08-01)

Multi-agent machine learning : a reinforcement approach /
Bằng: Schwartz, Howard M., author
Được phát hành: ([201)

Multi-Agent Reinforcement Learning: A Review of Challenges and Applications
Bằng: Lorenzo Canese, et al.
Được phát hành: (2021-05-01)

Extensible Hierarchical Multi-Agent Reinforcement-Learning Algorithm in Traffic Signal Control
Bằng: Pengqian Zhao, et al.
Được phát hành: (2022-12-01)

A Cooperative Multi-Agent Reinforcement Learning Method Based on Coordination Degree
Bằng: Haoyan Cui, et al.
Được phát hành: (2021-01-01)

Exploring and Exploiting Conditioning of Reinforcement Learning Agents
Bằng: Arip Asadulaev, et al.
Được phát hành: (2020-01-01)

Emergence of chemotactic strategies with multi-agent reinforcement learning
Bằng: Samuel Tovey, et al.
Được phát hành: (2024-01-01)

Multi agent physics informed reinforcement learning for waterflooding optimization
Bằng: Ramez Abdalla, et al.
Được phát hành: (2025-03-01)

Message Action Adapter Framework in Multi-Agent Reinforcement Learning
Bằng: Bumjin Park, et al.
Được phát hành: (2024-11-01)

Design and application of deep reinforcement learning algorithms based on unbiased exploration strategies for value functions
Bằng: Pingli Lv
Được phát hành: (2024-08-01)

Towards a multi-agent reinforcement learning approach for joint sensing and sharing in cognitive radio networks
Bằng: Kagiso Rapetswa, et al.
Được phát hành: (2023-03-01)

Goal modelling for deep reinforcement learning agents
Bằng: Leung, Jonathan, et al.
Được phát hành: (2022)

An Efficient Centralized Multi-Agent Reinforcement Learner for Cooperative Tasks
Bằng: Dengyu Liao, et al.
Được phát hành: (2023-01-01)

Multi-Agent Reinforcement Learning for Online Food Delivery with Location Privacy Preservation
Bằng: Suleiman Abahussein, et al.
Được phát hành: (2023-11-01)

Reinforcement Learning-Based Autonomous Soccer Agents: A Study in Multi-Agent Coordination and Strategy Development
Bằng: Biplov Paneru, et al.
Được phát hành: (2025-01-01)

Scaling Up Multi-Agent Reinforcement Learning: An Extensive Survey on Scalability Issues
Bằng: Dingbang Liu, et al.
Được phát hành: (2024-01-01)

Multi-agent reinforcement learning for autonomous vehicles: a survey
Bằng: Joris Dinneweth, et al.
Được phát hành: (2022-11-01)

Multi-Level Credit Assignment for Cooperative Multi-Agent Reinforcement Learning
Bằng: Lei Feng, et al.
Được phát hành: (2022-07-01)

GenFedRL: a general federated reinforcement learning framework for deep reinforcement learning agents
Bằng: Biao JIN, et al.
Được phát hành: (2023-06-01)

GenFedRL: a general federated reinforcement learning framework for deep reinforcement learning agents
Bằng: Biao JIN, et al.
Được phát hành: (2023-06-01)

Fit for purpose: Modeling wholesale electricity markets realistically with multi-agent deep reinforcement learning
Bằng: Nick Harder, et al.
Được phát hành: (2023-10-01)

A review of the applications of multi-agent reinforcement learning in smart factories
Bằng: Fouad Bahrpeyma, et al.
Được phát hành: (2022-12-01)

Towards Pareto-optimal energy management in integrated energy systems: A multi-agent and multi-objective deep reinforcement learning approach
Bằng: Jiaming Dou, et al.
Được phát hành: (2024-08-01)

Environmental-Impact-Based Multi-Agent Reinforcement Learning
Bằng: Farinaz Alamiyan-Harandi, et al.
Được phát hành: (2024-07-01)

Comparative Evaluation of Different Multi-Agent Reinforcement Learning Mechanisms in Condenser Water System Control
Bằng: Shunian Qiu, et al.
Được phát hành: (2022-07-01)

A Multitask-Based Transfer Framework for Cooperative Multi-Agent Reinforcement Learning
Bằng: Cheng Hu, et al.
Được phát hành: (2025-02-01)

Multi-Agent Deep Reinforcement Learning for Multi-Robot Applications: A Survey
Bằng: James Orr, et al.
Được phát hành: (2023-03-01)

Multi-Agent Hierarchical Graph Attention Actor–Critic Reinforcement Learning
Bằng: Tongyue Li, et al.
Được phát hành: (2024-12-01)