Abstract— Q-learning is a technique used to compute an optimal policy for a controlled Markov chain based on observations of the system controlled using a non-optimal policy. It ...
We consider the problem of cooperative multiagent planning under uncertainty, formalized as a decentralized partially observable Markov decision process (Dec-POMDP). Unfortunately...
Matthijs T. J. Spaan, Frans A. Oliehoek, Nikos A. ...
Web search engines face an extremely heterogeneous user population from web novices to highly skilled experts. Currently, the search strategies of the experienced web searchers ar...
Planning under uncertainty is an important and challenging problem in multiagent systems. Multiagent Partially Observable Markov Decision Processes (MPOMDPs) provide a powerful fr...
This paper formulates in the first part some requirements for a certain sort of computational argumentation systems, namely those which are designed for a very specific purpose: to...