In multiagent planning, it is often convenient to view a problem as two subproblems: agent local planning and coordination. Thus, we can classify agent activities into two categor...
Partially observable Markov decision processes (POMDPs) are widely used for planning under uncertainty. In many applications, the huge size of the POMDP state space makes straightf...
Joni Pajarinen, Jaakko Peltonen, Ari Hottinen, Mik...
We adopt the decision-theoretic principle of expected utility maximization as a paradigm for designing autonomous rational agents operating in multi-agent environments. We use the...
A problem of planning for cooperative teams under uncertainty is a crucial one in multiagent systems. Decentralized partially observable Markov decision processes (DECPOMDPs) prov...
The ability for an agent to reason under uncertainty is crucial for many planning applications, since an agent rarely has access to complete, error-free information about its envi...