This paper deals with a congestion control framework for elastic and real-time traffic, where the user's application is associated with a utility function. We allow users to ...
: In order to scale to problems with large or continuous state-spaces, reinforcement learning algorithms need to be combined with function approximation techniques. The majority of...
Distributed partially observable Markov decision problems (POMDPs) have emerged as a popular decision-theoretic approach for planning for multiagent teams, where it is imperative f...
Combinatorial auctions (CAs) have emerged as an important model in economics and show promise as a useful tool for tackling resource allocation in AI. Unfortunately, winner determ...
We study two properties of coalition formation algorithms, very important for their application in real-life scenarios: robustness and tolerance to some agent misbehaviors. The st...