An issue that is critical for the application of Markov decision processes MDPs to realistic problems is how the complexity of planning scales with the size of the MDP. In stochas...
We present two new algorithms for finding optimal strategies for discounted, infinite-horizon, Deterministic Markov Decision Processes (DMDP). The first one is an adaptation of...
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...
Abstract— This paper is concerned with the robust stabilization of a class of stochastic large-scale systems. The uncertainties satisfy integral quadratic constraints. The random...
Junlin Xiong, Valery A. Ugrinovskii, Ian R. Peters...
—This paper presents a method for learning decision theoretic models of human behaviors from video data. Our system learns relationships between the movements of a person, the co...