One jump ahead: challenging human supremacy in checkers
One jump ahead: challenging human supremacy in checkers
Do the thing right: an architecture for action-expression
AGENTS '98 Proceedings of the second international conference on Autonomous agents
AI and the Entertainment Industry
IEEE Intelligent Systems
Adaptive game AI with dynamic scripting
Machine Learning
Real-time evolution of neural networks in the NERO video game
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
The behavior-oriented design of modular agent intelligence
NODe'02 Proceedings of the NODe 2002 agent-related conference on Agent technologies, infrastructures, tools, and applications for E-services
Evolutionary computation and games
IEEE Computational Intelligence Magazine
Evolving an expert checkers playing program without using humanexpertise
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A subsumptive, hierarchical, and distributed vision-based architecture for smart robotics
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Learning tactical human behavior through observation of human performance
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A Potential Field Model Using Generalized Sigmoid Functions
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Characterizing Game Dynamics in Two-Player Strategy Games Using Network Motifs
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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This paper examines the design of a controller that is computationally efficient yet demonstrates highly competitive performance for a real time simulated car racing game. In turn based games, the game artificial intelligence (AI) is able to compensate for its lack of game reasoning by evaluating board positions millions of times faster than the human player. However, such extreme resource requirements are impractical for fast paced and real time games, i.e. racing games, sports simulators, first person shooters and real time strategy games. This paper proposes and describes in detail an evolved behaviour based controller that combines the good response time of behaviour based systems and search capability of evolutionary algorithms to evolve competitive driving skills for a real time car racing game. The proposed controller is tested against the top five participants of the Simulated Car Racing Competition held during the 2007 IEEE Congress on Evolutionary Computation (CEC) to evaluate its generalization performance against previously unseen controllers. The proposed behaviour based controller is able to outperform all its opponents in direct competition, and is also the most computationally efficient.