The BDI agent model comprises a simple but efficient folk psychological framework of mentalistic notions usable for modeling rational agent behaviour. Nevertheless, despite its u...
Alexander Pokahr, Lars Braubach, Winfried Lamersdo...
Partially observable Markov decision process (POMDP) is commonly used to model a stochastic environment with unobservable states for supporting optimal decision making. Computing ...
This paper describes an agent-based recommendation system developed to support knowledge acquisition and sharing processes. Its purpose is to aid the process of community building...
Mauro F. Koyama, Olga Nabuco, Francisco Edeneziano...
Our previous research presents a methodology of cooperative problem solving for BDI systems, based on a complete formal theory. This covers both a static part, defining individua...
Marcin Dziubinski, Rineke Verbrugge, Barbara Dunin...
Being able to trust in a system behavior is of prime importance, particularly within the context of critical applications as embedded or real-time systems. We want to ensure that ...
Caroline Chopinaud, Amal El Fallah-Seghrouchni, Pa...
Multiagent Bayesian networks (MABNs) are a powerful new framework for uncertainty management in a distributed environment. In a MABN, a collective joint probability distribution i...
Choosing when to communicate is a fundamental problem in multi-agent systems. This problem becomes particularly hard when communication is constrained and each agent has different...
Raphen Becker, Victor R. Lesser, Shlomo Zilberstei...
Cooperative negotiation is proved to be an effective paradigm to solve complex dynamic multi-objective problems in which each objective is associated to an agent. When the multi-o...
This paper proposes a middleware based on the multi-agent paradigm. Our proposition enables agents to locate and to interact easily with heterogeneous services and information pro...