TY - GEN
T1 - Multiobjective techniques for the use of state in genetic programming applied to simulated car racing
AU - Agapitos, Alexandras
AU - Togelius, Julian
AU - Lucas, Simon M.
PY - 2007
Y1 - 2007
N2 - Multi-objective optimisation is applied to encourage the effective use of state variables in car controlling programs evolved using Genetic Programming. Three different metrics for measuring the use of state within a program are introduced. Comparisons are performed among multi- and single-objective fitness functions with respect to learning speed and final fitness of evolved individuals, and attempts are made at understanding whether there is a trade-off between good performance and stateful controllers in this problem domain.
AB - Multi-objective optimisation is applied to encourage the effective use of state variables in car controlling programs evolved using Genetic Programming. Three different metrics for measuring the use of state within a program are introduced. Comparisons are performed among multi- and single-objective fitness functions with respect to learning speed and final fitness of evolved individuals, and attempts are made at understanding whether there is a trade-off between good performance and stateful controllers in this problem domain.
UR - http://www.scopus.com/inward/record.url?scp=57349189257&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=57349189257&partnerID=8YFLogxK
U2 - 10.1109/CEC.2007.4424659
DO - 10.1109/CEC.2007.4424659
M3 - Conference contribution
AN - SCOPUS:57349189257
SN - 1424413400
SN - 9781424413409
T3 - 2007 IEEE Congress on Evolutionary Computation, CEC 2007
SP - 1562
EP - 1569
BT - 2007 IEEE Congress on Evolutionary Computation, CEC 2007
T2 - 2007 IEEE Congress on Evolutionary Computation, CEC 2007
Y2 - 25 September 2007 through 28 September 2007
ER -