Multi-Objective Multi-Agent Decision Making: A Utility-based Analysis and Survey: JAAMAS Track

Many real-world decision problems are inherently multi-objective in nature and concern multiple actors, making multi-objective multi- agent systems a key domain to study. We argue that trade-offs between conflicting objective functions should be analysed on the basis of the utility that these trade-offs have for the users of a system. We develop a new taxonomy which classifies multi-objective multi-agent decision making settings, on the basis of the reward structures and utility functions. We analyse which solution concepts apply to the different settings in our taxonomy, which allows us to offer a structured view of the field and identify promising directions for future research.