Robust Model Equivalence using Stochastic Bisimulation for N-Agent Interactive DIDs
نویسندگان
چکیده
I-DIDs suffer disproportionately from the curse of dimensionality dominated by the exponential growth in the number of models over time. Previous methods for scaling I-DIDs identify notions of equivalence between models, such as behavioral equivalence (BE). But, this requires that the models be solved first. Also, model space compression across agents has not been previously investigated. We present a way to compress the space of models across agents, possibly with different frames, and do so without having to solve them first, using stochastic bisimulation. We test our approach on two non-cooperative partially observable domains with up to 20 agents.
منابع مشابه
Approximate 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 کاملApproximating Value Equivalence in Interactive Dynamic Influence Diagrams Using Behavioral Coverage
Interactive dynamic influence diagrams (I-DIDs) provide an explicit way of modeling how a subject agent solves decision making problems in the presence of other agents in a common setting. To optimize its decisions, the subject agent needs to predict the other agents’ behavior, that is generally obtained by solving their candidate models. This becomes extremely difficult since the model space m...
متن کاملA Value Equivalence Approach for Solving Interactive Dynamic Influence Diagrams
Interactive dynamic influence diagrams (I-DIDs) are recognized graphical models for sequential multiagent decision making under uncertainty. They represent the problem of how a subject agent acts in a common setting shared with other agents who may act in sophisticated ways. The difficulty in solving I-DIDs is mainly due to an exponentially growing space of candidate models ascribed to other ag...
متن کاملExploiting Model Equivalences for Solving Interactive Dynamic Influence Diagrams
We focus on the problem of sequential decision making in partially observable environments shared with other agents of uncertain types having similar or conflicting objectives. This problem has been previously formalized by multiple frameworks one of which is the interactive dynamic influence diagram (I-DID), which generalizes the well-known influence diagram to the multiagent setting. I-DIDs a...
متن کاملBehavioural equivalences for fluid stochastic Petri nets
We propose fluid equivalences that allow one to compare and reduce behaviour of labeled fluid stochastic Petri nets (LFSPNs) while preserving their discrete and continuous properties. We define a linear-time relation of fluid trace equivalence and its branching-time counterpart, fluid bisimulation equivalence. Both fluid relations take into account the essential features of the LFSPNs behaviour...
متن کامل