Autori: Rãzvan V. Florian

Editorial: S. Nolfi et al., Springer-Verlag, Lecture Notes in Artificial Intelligence, 4095, p.570-581, 2006.

Rezumat:

We evolve spiking neural networks that implement a seek-push-release drive for a simple simulated agent interacting with objects. The evolved agents display minimally-cognitive behavior, by switching as a function of context between the three sub-behaviors and by being able to discriminate relative object size. The neural controllers have either static synapses or synapses featuring spike-timing-dependent plasticity (STDP). Both types of networks are able to solve the task with similar efficacy, but networks with plastic synapses evolved faster. In the evolved networks, plasticity plays a minor role during the interaction with the environment and is used mostly to tune synapses when networks start to function.

Cuvinte cheie: artificial life, spiking neural networks, minimally cognitive behavior

URL: http://www.coneural.org/florian/papers/2006_florian_evolving_pushing.php