SIGGRAPH '94 Proceedings of the 21st annual conference on Computer graphics and interactive techniques
An Introduction to Genetic Algorithms
An Introduction to Genetic Algorithms
ECML '00 Proceedings of the 11th European Conference on Machine Learning
Generating flying creatures using body-brain co-evolution
Proceedings of the 2003 ACM SIGGRAPH/Eurographics symposium on Computer animation
Evolving Soccer Keepaway Players Through Task Decomposition
Machine Learning
Evolving Virtual Creatures and Catapults
Artificial Life
In silicon no one can hear you scream: evolving fighting creatures
EuroGP'08 Proceedings of the 11th European conference on Genetic programming
Evolution of vision capabilities in embodied virtual creatures
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Evolving a diversity of virtual creatures through novelty search and local competition
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Hierarchical task decomposition through symbiosis in reinforcement learning
Proceedings of the 14th annual conference on Genetic and evolutionary computation
Co-evolution of morphology and control of soft-bodied multicellular animats
Proceedings of the 14th annual conference on Genetic and evolutionary computation
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
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In the 19 years since Karl Sims' landmark publication on evolving virtual creatures (Sims, 1994), much of the future work he proposed has been implemented, having a significant impact on multiple fields including graphics, evolutionary computation, and artificial life. There has, however been one notable exception to this progress. Despite the potential benefits, there has been no clear increase in the behavioral complexity of evolved virtual creatures (EVCs) beyond the light following demonstrated in Sims' original work. This paper presents an open-ended method to move beyond this limit, making use of high-level human input in the form of a syllabus of intermediate learning tasks--along with mechanisms for preservation, reuse, and combination of previously learned tasks. This method (named ESP for its three components: encapsulation, syllabus, and pandemonium) is employed to evolve a virtual creature with behavioral complexity that clearly exceeds previously achieved levels. ESP thus demonstrates that EVCs may indeed have the potential to one day rival the behavioral complexity--and therefore the entertainment value--of their non-virtual counterparts.