Genetic programming may be seen as a recent incarnation of a long-held goal in evolutionary computation: to develop actual computational devices through evolutionary search. Geneti...
Many challenges remain in the development of tactical planning systems that will enable automated, cooperative replanning of routes and mission assignments for multiple unmanned gr...
Talib S. Hussain, David J. Montana, Gordon Vidaver
Abstract. Bloat control is an important aspect of evolutionary computation methods, such as genetic programming, which must deal with genomes of arbitrary size. We introduce three ...
Learning Deterministic Finite Automata (DFA) is a hard task that has been much studied within machine learning and evolutionary computation research. This paper presents a new met...
Although well understood in the single-agent framework, the use of traditional reinforcement learning (RL) algorithms in multi-agent systems (MAS) is not always justified. The fe...