Decentralized partially observable Markov decision processes (Dec-POMDPs) constitute an expressive framework for multiagent planning under uncertainty, but solving them is provabl...
Frans A. Oliehoek, Matthijs T. J. Spaan, Shimon Wh...
Researchers in the field of multiagent sequential decision making have commonly used the terms “weakly-coupled” and “loosely-coupled” to qualitatively classify problems i...
In this paper, we propose a policy gradient reinforcement learning algorithm to address transition-independent Dec-POMDPs. This approach aims at implicitly exploiting the locality...
Shading complex materials such as acquired reflectances in multilight environments is computationally expensive. Estimating the shading integral requires multiple samples of the ...
Mahdi M. Bagher, Cyril Soler, Kartic Subr, Laurent...
We describe several approaches for using prosodic features of speech and audio localization to control interactive applications. This information can be applied to parameter contr...