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A simulation software package (UFLibrary) implementing the utility function (UF) method for behavior selection in autonomous robots, is introduced and described by means of an example involving a simple exploration robot equipped with a repertoire of five different behaviors. The UFLibrary (as indeed the UF method itself) is aimed at providing a rapid yet reliable and generally applicable procedure for generating behavior selection systems for autonomous robots, while at the same time minimizing the amount of hand-coding related to the activation of behaviors. It is demonstrated how the UFLibrary allows a user to rapidly implement individual behaviors and to set up and carry out simulations of a robot in its arena, in order to generate and optimize, by means of an evolutionary algorithm, the behavior selection system of the robot. [ABSTRACT FROM AUTHOR]

The generation of a complete robotic brain for locomotion based on the utility function (UF) method for behavioral organization is demonstrated. A simulated, single-legged hopping robot is considered, and a two-stage process is used for generating the robotic brain. First, individual behaviors are constructed through artificial evolution of recurrent neural networks (RNNs). Thereafter, a behavioral organizer is generated through evolutionary optimization of utility functions. Two systems are considered: a simplified model with trivial dynamics, as well as a model using full newtonian dynamics. In both cases, the UF method was able to generate an adequate behavioral organizer, which allowed the robot to perform its primary task of moving through an arena, while avoiding collisions with obstacles and keeping the batteries sufficiently charged. The results for the simplified model were better than those for the dynamical model, a fact that could be attributed to the poor performance of the individual behaviors (implemented as RNNs) during extended operation. [ABSTRACT FROM AUTHOR]