Conference Publication Details
Mandatory Fields
Mannion, P;Duggan, J;Howley, E
AAMAS'17: PROCEEDINGS OF THE 16TH INTERNATIONAL CONFERENCE ON AUTONOMOUS AGENTS AND MULTIAGENT SYSTEMS
A Theoretical and Empirical Analysis of Reward Transformations in Multi-Objective Stochastic Games
2017
January
Published
1
WOS: 1 ()
Optional Fields
1625
1627
Reward shaping has been proposed as a means to address the credit assignment problem in Multi-Agent Systems (MAS). Two popular shaping methods are Potential-Based Reward Shaping and difference rewards, and both have been shown to improve learning speed and the quality of joint policies learned by agents in single-objective MAS. In this work we discuss the theoretical implications of applying these approaches to multi-objective MAS, and evaluate their efficacy using a new multi-objective benchmark domain where the true set of Pareto optimal system utilities is known.
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