Distributed Partially Observable Markov Decision Problems (Distributed POMDPs) are evolving as a popular approach for modeling multiagent systems, and many different algorithms ha...
In environmental and natural resource planning domains actions are taken at a large number of locations over multiple time periods. These problems have enormous state and action s...
This paper presents a complete solution to estimating a scene’s 3D geometry and appearance from multiple 2D images by using a statistical inverse ray tracing method. Instead of ...
Decentralized partially observable Markov decision processes (DEC-POMDPs) form a general framework for planning for groups of cooperating agents that inhabit a stochastic and part...
Matthijs T. J. Spaan, Geoffrey J. Gordon, Nikos A....
This paper presents a new framework for accumulating beliefs in spoken dialogue systems. The technique is based on updating a Bayesian Network that represents the underlying state...