Reinforcement Learning with Multiple Shared Rewards

Author:

Guisi Douglas M.,Ribeiro Richardson,Teixeira Marcelo,Borges Andre P.,Enembreck Fabricio

Publisher

Elsevier BV

Subject

General Engineering

Reference21 articles.

1. Multiagent learning in the presence of memory-bounded agents;Chakraborty;Autonomous Agents and Multi-Agent Systems,2014

2. How situated agents can learn to cooperate by monitoring their neighbors’ satisfaction;Chapelle;ECAI,2002

3. DeLoach, S. and Valenzuela, J. (2007). An agent environment interaction model. In Padgham, L. and Zambonelli, F., editors, Agent-Oriented Software Engineering VII, volume 4405 of Lecture Notes in Computer Science, pages 1-18. Springer Berlin Heidelberg.

4. Devlin, S., Yliniemi, L., Kudenko, D., and Tumer, K. (2014). Potential-based difference rewards for multiagent reinforcement learning. In Proceedings of the 2014 International Conference on Autonomous Agents and Multi-agent Systems, AAMAS’14, pages. 165-172, Richland, SC.

5. Efthymiadis, K. and Kudenko, D. (2015). Knowledge revision for reinforcement learning with abstract mdps. In Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems, AAMAS’15, pages 763-770, Richland, SC.

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