Publication - Combining Dynamic Reward Shaping and Action Shaping for Coordinating Multi-Agent Learning

Authors: Zhu, Xiangbin; Zhang, Chongjie; Lesser, Victor
Title: Combining Dynamic Reward Shaping and Action Shaping for Coordinating Multi-Agent Learning
Abstract: Coordinating multi-agent reinforcement learning provides a promising approach to scaling learning in large cooperative multi-agent systems. It allows agents to learn local decision policies based on their local observations and rewards, and, meanwhile, coordinates agents´ learning processes to ensure the global learning performance. One key question is that how coordination mechanisms impact learning algorithms so that agents´ learning processes are guided and coordinated. This paper presents a new shaping approach that effectively integrates coordination mechanisms into local learning processes. This shaping approach uses two-level agent organization structures and combines reward shaping and action shaping. The higher-level agents dynamically and periodically produce the shaping heuristic knowledge based on the learning status of the lower-level agents. The lower-level agents then uses this knowledge to coordinate their local learning processes with other agents. Experimental results show our approach effectively speeds up the convergence of multi-agent learning in large systems.
Keywords: Learning, Multi-Agent Systems, Organizational Control
Publication: Proc. of 2013 IEEE/WIC/ACM International Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT), Vol: 2, pp. 321 - 328
Location: Atlanta, GA
Publisher: IEEE Computer Society Press
Date: 2013
Sources: PDF: /Documents/lesser/zhu_IAT13.pdf
HTML: http://doi.ieeecomputersociety.org/10.1109/WI-IAT.2013.127
Reference: Xiangbin Zhu, Chongjie Zhang, Victor Lesser (2013). "Combining Dynamic Reward Shaping and Action Shaping for Coordinating Multi-agent Learning," Proc. of IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT), Vol. 2, pp. 321-328. [View Details]

bibtex:
@inproceedings{Zhu-523,
  author    = "Xiangbin Zhu and Chongjie Zhang and Victor Lesser",
  title     = "{Combining Dynamic Reward Shaping and Action
               Shaping for Coordinating Multi-Agent Learning}",
  booktitle = "Proc. of 2013 IEEE/WIC/ACM International
               Conferences on Web Intelligence (WI) and
               Intelligent Agent Technologies (IAT)",
  volume    = "2",
  publisher = "IEEE Computer Society Press",
  pages     = "321-328",
  year      = "2013",
  address   = "Atlanta, GA",
  url       = "http://mas.cs.umass.edu/paper/523",
}