Spiking Neural Controllers for Pushing Objects Around

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.