This paper is concerned with estimating the effects of actions from causal assumptions, represented concisely as a directed graph, and statistical knowledge, given as a probabilit...
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...
This paper contributes to solve effectively stochastic resource allocation problems known to be NP-Complete. To address this complex resource management problem, the merging of tw...
Currently, applications that focus on providing conversations with virtual humans require extensive work to create robust conversational models. We present a new approach called Hu...
This paper uses partially observable Markov decision processes (POMDP’s) as a basic framework for MultiAgent planning. We distinguish three perspectives: first one is that of a...
Bharaneedharan Rathnasabapathy, Piotr J. Gmytrasie...