Experience-Based Reinforcement Learning to Acquire Effective Behavior in a Multi-agent Domain-Reference-Cited by-同舟云学术

Experience-Based Reinforcement Learning to Acquire Effective Behavior in a Multi-agent Domain

Published:2000 Issue: Volume: Page:125-135
ISSN:0302-9743
Container-title:PRICAI 2000 Topics in Artificial Intelligence
language:
Short-container-title:

Author:

Arai Sachiyo,Sycara Katia,Payne Terry R.

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/3-540-44533-1_16

Reference17 articles.

1. Arai, S., Miyazaki, K., Kobayashi, S.: Generating Cooperative Behavior by Multi-Agent Reinforcement Learning, Proceedings of 6th European Workshop on Learning Robots p111–120 (1997).

2. Clement, J. Bradley and Durfee, H. Edmund: Top-Down Search for Coordinating the Hierarchical Plans of Multiple Agents. Proceedings of the 3rd International Conference on Autonomous Agents, pp252–259 (1999).

3. Chrisman, L.: Reinforcement learning with perceptual aliasing: The Perceptual Distinctions Approach, Proceedings of the 10th National Conference on Artificial Intelligence, pp.183–188 (1992).

4. Firby, R.J., An Investigation into Reactive Planning in complex Domains, Proceedings of 10th National Conference on Artificial Intelligence’ 87, 202–206 (1987).

5. Georgeff, M.P.: Communication and interaction in Multi-agent Planning, Proceedings of the 3rd National Conference on Artificial Intelligence, pp.125–129 (1983).

Cited by 10 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Indoor Pursuit-Evasion with Hybrid Hierarchical Partially Observable Markov Decision Processes for Multi-robot Systems;Distributed Autonomous Robotic Systems;2019

2. Knowledge Co-creation Framework: Novel Transfer Learning Method in Heterogeneous Multi-agent Systems;Springer Tracts in Advanced Robotics;2016

3. Hierarchical Transfer Learning in Heterogeneous Multi-agent Systems;Transactions of the Society of Instrument and Control Engineers;2015

4. A Question of Balance;Transactions on Computational Collective Intelligence XX;2015

5. A reward allocation method for reinforcement learning in stabilizing control tasks;Artificial Life and Robotics;2014-07-29