In this paper, we investigate Reinforcement learning (RL) in multi-agent systems (MAS) from an evolutionary dynamical perspective. Typical for a MAS is that the environment is not ...
Karl Tuyls, Pieter Jan't Hoen, Bram Vanschoenwinke...
This paper presents an evolutionary artificial neural network approach based on the pareto differential evolution algorithm augmented with local search for the prediction of breas...
— In this article we present results from experiments where a edge detector was learned from scratch by EANT2, a method for evolutionary reinforcement learning. The detector is c...
Abstract. We aim to construct an automatic system for the discovery of collision-based universal cellular automata that simulate Turing machines in their space-time dynamics using ...
This article presents a model for DNA sequence alignment. In our model, a finite state automaton writes two-dimensional maps of nucleotide sequences. An evolutionary method for se...