Main stream approaches in distributed artificial intelligence (DAI) are essentially logic-based. Little has been reported to explore probabilistic approach in DAI. On the other han...
Abstract--This paper is focusing on exact Bayesian reasoning in systems of agents, which represent weakly coupled processing modules supporting collaborative inference through mess...
In this paper, a model is proposed for multi-agent probabilistic reasoning in a distributed environment. Unlike other methods, this model is capable of processing input in a truly...
In this paper, we introduce a probabilistic relational data model as the basis for developing multi-agent probabilistic reasoning systems. Since our model subsumes the traditional...
This paper introduces design principles for modular Bayesian fusion systems which can (i) cope with large quantities of heterogeneous information and (ii) can adapt to changing co...
Gregor Pavlin, Patrick de Oude, Marinus Maris, Jan...