Abstract a paradigm of modern Machine Learning (ML) which uses rewards and punishments to guide the learning process. One of the central ideas of RL is learning by “direct-online...
A new family of "Distribution Replacement” operators for use in steady state genetic algorithms is presented. Distribution replacement enforces the members of the populatio...
Real life optimization problems often require finding optimal solution to complex high dimensional, multimodal problems involving computationally very expensive fitness function e...
The topological properties of a network directly impact the flow of information through a system. In evolving populations, the topology of inter-individual interactions affects th...
Spatio-temporal network is defined by a set of nodes, and a set of edges, where the properties of nodes and edges may vary over time. Such networks are encountered in a variety of...