No abstract

Wilson introduced XCSF as a successor to XCS. The major development of XCSF is the concept of a computed prediction. The efficiency of XCSF in dealing with numerical input and continuous payoff has been demonstrated. However, the possible actions must always be determined in advance. Yet domains such as robot control require numerical actions, so that neither XCS nor XCSF with their discrete actions can yield high performance. This paper studies computed action in XCSF, where the action is continuous with respect to the input state. In comparison with Wilson's architecture for continuous action, our XCSF version, called XCSFCA, proves to be more efficient.

Form generation or morphogenesis is one of the main stages of both artificial and natural development. This paper provides results from experiments in which a genetic algorithm (GA) was used to evolve cellular automata (CA) to produce predefined 2D and 3D shapes. The GA worked by evolving the CA rule table and the number of iterations that the model was to run. After the final chromosomes were obtained for all shapes, the CA model was allowed to run starting with a single cell in the middle of the lattice until the allowed number of iterations was reached and a shape was formed. In all cases, mean fitness values of evolved chromosomes were above 80%.

No abstract

No abstract