Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
An evolved, vision-based behavioral model of coordinated group motion
Proceedings of the second international conference on From animals to animats 2 : simulation of adaptive behavior: simulation of adaptive behavior
Genetic programming applied to Othello: introducing students to machine learning research
SIGCSE '99 The proceedings of the thirtieth SIGCSE technical symposium on Computer science education
Blondie24: playing at the edge of AI
Blondie24: playing at the edge of AI
Methods for Competitive Co-Evolution: Finding Opponents Worth Beating
Proceedings of the 6th International Conference on Genetic Algorithms
Fitness Distance Correlation as a Measure of Problem Difficulty for Genetic Algorithms
Proceedings of the 6th International Conference on Genetic Algorithms
Evolving Beharioral Strategies in Predators and Prey
IJCAI '95 Proceedings of the Workshop on Adaption and Learning in Multi-Agent Systems
Co-evolving Soccer Softbot Team Coordination with Genetic Programming
RoboCup-97: Robot Soccer World Cup I
AI Techniques for Game Programming
AI Techniques for Game Programming
Evolving cooperative strategies for UAV teams
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Genetically programmed strategies for chess endgame
Proceedings of the 8th annual conference on Genetic and evolutionary computation
AI Game Development
Fitness-proportional negative slope coefficient as a hardness measure for genetic algorithms
Proceedings of the 9th annual conference on Genetic and evolutionary computation
A phenotypic analysis of GP-evolved team behaviours
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Evolving teamwork and coordination with genetic programming
GECCO '96 Proceedings of the 1st annual conference on Genetic and evolutionary computation
Negative slope coefficient: a measure to characterize genetic programming fitness landscapes
EuroGP'06 Proceedings of the 9th European conference on Genetic Programming
GP-EndChess: using genetic programming to evolve chess endgame players
EuroGP'05 Proceedings of the 8th European conference on Genetic Programming
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This paper investigates how varying the difficulty of the environment can affect the evolution of team behaviour in a combative game setting. The difficulty of the environment is altered by varying the perceptual capabilities of the agents in the game. The behaviours of the agents are evolved using a genetic program. These experiments show that the level of difficulty of the environment does have an impact on the evolvability of effective team behaviours; i.e. simpler environments are more conducive to the evolution of effective team behaviours than more difficult environments. In addition, the experiments show that no one best solution from any environment is optimal for all environments.