Evolving Shepherding Behavior with Genetic Programming Algorithms

Cooperative Co-Evolving Neural Networks for Robosoccer Simulation

Applying and Comparing Evolutionary Algorithms for Robot Tanks

Robocode, an open source tank combat game, has become immensely popular based on both its educational as well as its “fun" value. Throughout the years, many interesting AIs have been developed for Robocode, most of which were based on finite-state machines and were generally “hard-coded". The effects of employing evolutionary algorithms and machine learning on Robocode, however, have not been s...

Evolving simple software agents: Comparing genetic algorithm and genetic programming performance

This paper investigates the relative eeciency of genetic algorithms and genetic programming in evolving simple software agents. The problem domain consists of an autonomous food-gathering agent placed on a square grid of hundred cells with food units spread evenly over the grid. Initial results show that evolving the agent using GP requires less eeort than with GA. Nevertheless, further investi...

Co-evolving Soccer Softbot Team Coordination with Genetic Programming

In this paper we explain how we applied genetic programming to behavior-based team coordination in the RoboCup Soccer Server domain. Genetic programming is a promising new method for automatically generating functions and algorithms through natural selection. In contrast to other learning methods, genetic programming’s automatic programming makes it a natural approach for developing algorithmic...

Evolving a Sort: Lessons in Genetic Programming

In applying the Genetic Programming paradigm to the task of evolving iterative sorting algorithms, a variety of interesting lessons were learned. With proper selection of the primitives, sorting algorithms were evolved that are both general and non-trivial. The sorting problem was then used as a testbed to evaluate the value of several alternative parameters, with some small gains shown. The va...