Agents often want to protect private information, while at the same acting upon the information. These two desires are in conflict, and this conflict can be modeled in strategic...
This paper studies the quality of service (QoS) provision problem in noncooperative networks where applications or users are selsh and routers implement generalized processor sha...
Abstract. Most of multi-agent reinforcement learning algorithms aim to converge to a Nash equilibrium, but a Nash equilibrium does not necessarily mean a desirable result. On the o...
We introduce choice logic programs as negation-free datalog programs that allow rules to have exclusive-only (possibly empty) disjunctions in the head. Such programs naturally mod...
Future agent applications will increasingly represent human users autonomously or semi-autonomously in strategic interactions with similar entities. Hence, there is a growing need...