Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Genetic programming II: automatic discovery of reusable programs
Genetic programming II: automatic discovery of reusable programs
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
Research in human-level AI using computer games
Communications of the ACM - Internet abuse in the workplace and Game engines in scientific research
A methodology for missile countermeasures optimization under uncertainty
Evolutionary Computation
Generation of Time-Delay Algorithms for Anti-Air Missiles Using Genetic Programming
Proceedings of the EvoWorkshops on Applications of Evolutionary Computing
An Investigation of an Adaptive Poker Player
AI '01 Proceedings of the 14th Australian Joint Conference on Artificial Intelligence: Advances in Artificial Intelligence
Evolving Chess Playing Programs
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
Evolving an expert checkers playing program without using humanexpertise
IEEE Transactions on Evolutionary Computation
The identification and exploitation of dormancy in genetic programming
Genetic Programming and Evolvable Machines
Evolving driving controllers using genetic programming
CIG'09 Proceedings of the 5th international conference on Computational Intelligence and Games
Instruction selection for ARM/Thumb processors based on a multi-objective ant algorithm
CSR'06 Proceedings of the First international computer science conference on Theory and Applications
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Computer games and simulations are commonly used as a basis for analysing and developing battlefield strategies. Such strategies are usually programmed explicitly, but it is also possible to generate them automatically via the use of evolutionary programming techniques. We focus in particular on the use of genetic programming to evolve strategies for a single defender facing multiple simultaneous attacks. By expressing the problem domain in the form of a ‘Space Invaders' game, we show that it is possible to evolve winning strategies for an increasingly complex sequence of scenarios.