Interactive Dynamic Influence Diagrams for Relational Agents

Interactive Dynamic Influence Diagrams (I-DIDs) are a general decision making framework for multiple agents that are either collaborative or competitive. The framework allows for agents to plan individually at their own level in the context of other agents acting and observing in a partially observable environment. Most of the I-DID techniques focus on a simple setting of two agents in which one subject agent models the other agent. Extending the approaches to multiple (>2) agents becomes very complicated since the subject agent needs to model all other agents that themselves are modelled as the I-DIDs. In this paper, we exploit potential relations of the modelled agents and avoid to model the other agents individually from the perspective of the subject agent. We show the preliminary results from the investigation and discuss further research development on learning relations between multiple agents for new I-DID solutions.