Solving multiagent planning problems modeled as DECPOMDPs is an important challenge. These models are often solved by using dynamic programming, but the high resource usage of cur...
Christopher Amato, Jilles Steeve Dibangoye, Shlomo...
Partially-observable Markov decision processes (POMDPs) provide a powerful model for sequential decision-making problems with partially-observed state and are known to have (appro...