Learning Agents' Relations in Interactive Multiagent Dynamic Influence Diagrams
نویسندگان
چکیده
منابع مشابه
Learning Behaviors in Agents Systems with Interactive Dynamic Influence Diagrams
Interactive dynamic influence diagrams (I-DIDs) are a well recognized decision model that explicitly considers how multiagent interaction affects individual decision making. To predict behavior of other agents, I-DIDs require models of the other agents to be known ahead of time and manually encoded. This becomes a barrier to I-DID applications in a human-agent interaction setting, such as devel...
متن کاملApproximate solutions of interactive dynamic influence diagrams using ε-behavioral equivalence
Interactive dynamic influence diagrams (I-DID) are graphical models for sequential decision making in uncertain settings shared by other agents. Algorithms for solving I-DIDs face the challenge of an exponentially growing space of candidate models ascribed to other agents, over time. Pruning the behaviorally equivalent models is one way toward identifying a minimal model set. We seek to further...
متن کاملTeam behavior in interactive dynamic influence diagrams with applications to ad hoc teams
Planning for ad hoc teamwork is challenging because it involves agents collaborating without any prior coordination or communication. The focus is on principled methods for a single agent to cooperate with others. This motivates investigating the ad hoc teamwork problem in the context of individual decision making frameworks. However, individual decision making in multiagent settings faces the ...
متن کاملAn Influence Diagram Approach for Multiagent Time-Critical Dynamic Decision Modeling
Recent interests in multiagent dynamic decision modeling in partially observable multiagent environments have led to the development of several representation and inference methods. However, these methods have limited application under time-critical conditions where a trade-off between model quality and computational tractability is essential. We present a formal representation for modeling tim...
متن کاملModel identification in interactive influence diagrams using mutual information
Interactive influence diagrams (I-IDs) offer a transparent and intuitive representation for the decision-making problem in multiagent settings. They ascribe procedural models such as influence diagrams and I-IDs to model the behavior of other agents. Procedural models offer the benefit of understanding how others arrive at their behaviors. Accurate behavioral models of others facilitate optimal...
متن کامل