Programmable self-assembly using biologically-inspired multiagent control
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 1
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Morphological plasticity: environmentally driven morphogenesis
ECAL'05 Proceedings of the 8th European conference on Advances in Artificial Life
Genetic encoding of robot metamorphosis: how to evolve a glider with a genetic regulatory network
ANTS'10 Proceedings of the 7th international conference on Swarm intelligence
A developmental solution to (dynamic) capacitated arc routing problems using genetic programming
Proceedings of the 14th annual conference on Genetic and evolutionary computation
A study on scalable representations for evolutionary optimization of ground structures
Evolutionary Computation
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Developmental systems typically produce a phenotype through a generative process whose outcome depends on feedback from the environment. In most artificial developmental systems, this feedback occurs in one way: The environment affects the development process, but the development process does not necessarily affect the environment. Here we explore a condition where both the developing system and the environment affect each other on a similar timescale, thus resulting in system-environment dynamical interaction. Using a model inspired by termite nest construction, we demonstrate how evolution can exploit this system-environment dynamics to generate adaptive and self-repairing structure more efficiently than a purely reactive developmental system. Finally, we offer a metric to quantify the level of interaction and distinguish between reactive and interactive developmental systems.