Tree-based pruning for multiagent POMDPs with delayed communication
نویسندگان
چکیده
Multiagent POMDPs provide a powerful framework for optimal decision making under the assumption of instantaneous communication. We focus on a delayed communication setting (MPOMDP-DC), in which broadcast information is delayed by at most one time step. Such an assumption is in fact more appropriate for applications in which response time is critical. However, naive application of incremental pruning, the core of many state-of-the-art POMDP techniques, is intractable for MPOMDP-DCs. We overcome this problem by introducing a tree-based pruning technique. Experiments show that the method outperforms naive incremental pruning by orders of magnitude, allowing for the solution of larger problems.
منابع مشابه
Tree-Based Solution Methods for Multiagent POMDPs with Delayed Communication
Multiagent Partially Observable Markov Decision Processes (MPOMDPs) provide a powerful framework for optimal decision making under the assumption of instantaneous communication. We focus on a delayed communication setting (MPOMDP-DC), in which broadcasted information is delayed by at most one time step. This model allows agents to act on their most recent (private) observation. Such an assumpti...
متن کاملTowards Addressing Model Uncertainty: Robust Execution-time Coordination for Teamwork (Short Paper)
Despite their worst-case NEXP-complete planning complexity, DEC-POMDPs remain a popular framework for multiagent teamwork. This paper introduces effective teamwork under model uncertainty (i.e., potentially inaccurate transition and observation functions) as a novel challenge for DEC-POMDPs and presents MODERN, the first executioncentric framework for DEC-POMDPs explicitly motivated by addressi...
متن کاملRobust Execution-time Coordination in DEC-POMDPs Under Model Uncertainty
Despite their worst-case NEXP-complete planning complexity, DEC-POMDPs remain a popular framework for multiagent teamwork. This paper introduces effective teamwork under model uncertainty (i.e., potentially inaccurate transition and observation functions) as a novel challenge for DEC-POMDPs and presents MODERN, the first execution-centric framework for DEC-POMDPs explicitly motivated by address...
متن کاملSufficient Plan-Time Statistics for Decentralized POMDPs
Optimal decentralized decision making in a team of cooperative agents as formalized by decentralized POMDPs is a notoriously hard problem. A major obstacle is that the agents do not have access to a sufficient statistic during execution, which means that they need to base their actions on their histories of observations. A consequence is that even during off-line planning the choice of decision...
متن کاملDec-POMDPs with delayed communication
In this work we consider the problem of multiagent planning under sensing and acting uncertainty with a one time-step delay in communication. We adopt decentralized partially observable Markov processes (Dec-POMDPs) as our planning framework. When instantaneous and noise-free communication is available, agents can instantly share local observations. This effectively reduces the decentralized pl...
متن کامل