Causal Probabilistic Networks (CPNs), (a.k.a. Bayesian Networks, or Belief Networks) are well-established representations in biomedical applications such as decision support system...
Constantin F. Aliferis, Ioannis Tsamardinos, Alexa...
PAC-MDP algorithms approach the exploration-exploitation problem of reinforcement learning agents in an effective way which guarantees that with high probability, the algorithm pe...
We present an algorithm for polyline (and polygon) similarity testing that is based on the double-cross formalism. To determine the degree of similarity between two polylines, the...
This article presents a new system for automatically constructing and training radial basis function networks based on original evolutionary computing methods. This system, called...
This paper presents the dynamics of multiple learning agents from an evolutionary game theoretic perspective. We provide replicator dynamics models for cooperative coevolutionary ...