* 0-7803-7952-7/03/$17.00  2003 IEEE. Abstract In this paper we describe a method for the synthesis of robotic controllers using evolutionary techniques. A modified version of the recurrent neural network used for controlling the robots is evolved using Genetic Algorithm using the Variable Length Genotype approach where the genotype encodes the network. It has been discovered that separation o...

This paper is concerned with the improvement of reinforcement learning through the use of forbidden sequences of actions. A given reinforcement function can generate multiple effective behaviors. Each behavior is effective only considering the cumulative reward over time. It may not be the behavior expected by the designer. In this case, the usual solution is to modified the reinforcement funct...

This paper presents an adaptive method that allows mobile robots to learn cognitive maps of indoor environments incrementally and on-line. Our approach models the environment by means of a variable-resolution partitioning that discretizes the world in perceptually homogeneous regions. The resulting model incorporates both a compact geometrical representation of the environment and a topological...

This paper presents an emotion based process generating cognition through learning. Two models are described which investigates the possibilities of designing cognitive systems based on emotion. In order to test these models through experiments, we used a mobile robot simulator, Webots, modeling the real Khepera robot. The rst proposed model is the simplest since it uses only positive and negat...

Behavior-based artificial intelligent system is to derive the complicated behaviors by selecting appropriate one from a set of basic behaviors. Many robot systems have used behavior-based systems since the 1980’s. In this paper, we propose new method to create the sequences of behaviors appropriate to the changing environments by adding the function of learning with Learning Classifier System t...

|Behavior-based approach has been successfully applied to design the control system of a robot. This paper presents our approach, based on evolutionary algorithms , to program behavior-based robots automatically. Instead of handcoding all the behavior controllers or evolving an entire control system for an overall task, we suggest our approach at the intermediate level: it includes evolving beh...