Induction: processes of inference, learning, and discovery
Induction: processes of inference, learning, and discovery
A Rosetta stone for connectionism
CNLS '89 Proceedings of the ninth annual international conference of the Center for Nonlinear Studies on Self-organizing, Collective, and Cooperative Phenomena in Natural and Artificial Computing Networks on Emergent computation
Emergent computation
The performance of cooperative processes
Emergent computation
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Hidden order: how adaptation builds complexity
Hidden order: how adaptation builds complexity
Complexity
Artificial Life II
How TRURL Evolves Multiagent Worlds for Social Interaction Analysis
Community Computing and Support Systems, Social Interaction in Networked Communities [the book is based on the Kyoto Meeting on Social Interaction and Communityware, held in Kyoto, Japan, in June 1998]
Fuzzy learning in Zamin artificial world
Fuzzy Sets and Systems
In silicon no one can hear you scream: evolving fighting creatures
EuroGP'08 Proceedings of the 11th European conference on Genetic programming
AMT'10 Proceedings of the 6th international conference on Active media technology
Some problems in organic coding theory
General Theory of Information Transfer and Combinatorics
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Echo is a generic ecosystem model in which evolving agents are situated in a resource-limited environment. The Echo model is described, and the behavior of Echo is evaluated on two well-studied measures of ecological diversity: relative species abundance and the species-area scaling relation. In simulation experiments, these measures are used to compare the behavior of Echo with that of a neutral model, in which selection on agent genotypes is random. These simulations show that the evolutionary component of Echo makes a significant contribution to its behavior and that Echo shows good qualitative agreement with naturally occurring species abundance distributions and species-area scaling relations.