Grammatical Evolution: Evolutionary Automatic Programming in an Arbitrary Language
Grammatical Evolution: Evolutionary Automatic Programming in an Arbitrary Language
Biologically Inspired Algorithms for Financial Modelling (Natural Computing Series)
Biologically Inspired Algorithms for Financial Modelling (Natural Computing Series)
Robot gaits evolved by combining genetic algorithms and binary hill climbing
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Legged robot gait locus generation based on genetic algorithms
PCAR '06 Proceedings of the 2006 international symposium on Practical cognitive agents and robots
A review of gait optimization based on evolutionary computation
Applied Computational Intelligence and Soft Computing - Special issue on theory and applications of evolutionary computation
Using grammatical evolution to parameterise interactive 3D image generation
EvoApplications'11 Proceedings of the 2011 international conference on Applications of evolutionary computation - Volume Part II
Evolving interpolating models of net ecosystem CO2 exchange using grammatical evolution
EuroGP'12 Proceedings of the 15th European conference on Genetic Programming
A comparison of grammatical genetic programming grammars for controlling femtocell network coverage
Genetic Programming and Evolvable Machines
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Physics-based animal animations require data for realistic motion. This data is expensive to acquire through motion capture and inaccurate when estimated by an artist. Grammatical Evolution (GE) can be used to optimise pre-existing motion data or generate novel motions. Optimised motion data produces sustained locomotion in a physics-based model. To explore the use of GE for gait optimisation, the motion data of a walking horse, from a veterinary publication, is optimised for a physics-based horse model. The results of several grammars are presented and discussed. GE was found to be successful for optimising motion data using a grammar based on the concatenation of sinusoidal functions.