Abstract
We propose an evolving ecosystem approach to
evolving complex agent behaviour based on the principle of natural
selection. The agents start with very limited functional design
and morphology and neural controllers are concurrently evolved
as functional wholes. The agents are ‘grounded’ in an increasingly
complex environment by a complex model metabolism and interaction
dynamics. Furthermore, we introduce a novel criterion for
evaluating differential reproductive success aimed at maximising
evolutionary freedom. We also present first experimental results
suggesting that this approach may be conducive to widening the
scope of artificial evolution for the generation of agents exhibiting
non-trivial behaviours in a complex ecosystem.
evolving complex agent behaviour based on the principle of natural
selection. The agents start with very limited functional design
and morphology and neural controllers are concurrently evolved
as functional wholes. The agents are ‘grounded’ in an increasingly
complex environment by a complex model metabolism and interaction
dynamics. Furthermore, we introduce a novel criterion for
evaluating differential reproductive success aimed at maximising
evolutionary freedom. We also present first experimental results
suggesting that this approach may be conducive to widening the
scope of artificial evolution for the generation of agents exhibiting
non-trivial behaviours in a complex ecosystem.
| Original language | English |
|---|---|
| Title of host publication | Procs of the 2007 IEEE Symposium on Artificial Life (CI-SLife 2007) |
| Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
| Pages | 303-310 |
| Publication status | Published - 2007 |