Interactive dynamic influence diagrams
Kyle Polich, Piotr J. Gmytrasiewicz · 2007
Partially Observable Markov Decision Processes (POMDPs) emerged as the primary framework for decision-theoretic planning in single agent settings. Solutions to POMDPs are optimal plans which are conditional on future observations. Dynamic Influence Diagrams (DIDs) are computational representations of POMDPs which compute solutions for finite time horizons in an on-line fashion. Interactive POMDPs (I-POMDPs) [5] generalize POMDPs to multi-agent settings by including models of other agents in the state space. Interactive DIDs (I-DIDs), presented in this paper, are computational representations of I-POMDPs, and thus generalizations of DIDs. DIDs are themselves temporal generalizations of influence diagrams [6].