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The integration of modulatory neurons into evolutionary artificial neural networks is proposed here. A model of modulatory neurons was devised to describe a plasticity mechanism at the low level of synapses and neurons. No initial assumptions were made on ...
University of Birmingham, UK2008
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memory in biological neural networks. Similarly, artificial neural networks could benefit from modulatory dynamics when facing certain types of learning problem. Here we test this hypothesis by introducing modulatory neurons to enhance or dampen neural pla ...
MIT Press2008
An agent that deviates from a usual or previous course of action can be said to display novel or varying behaviour. Novelty of behaviour can be seen as the result of real or apparent randomness in decision making, which prevents an agent from repeating exa ...
Neuromodulation is thought to be one of the underlying principles of learning and memory in biological neural networks. Recent experiments have shown that neuroevolutionary methods benefit from neuromodulation in simple grid-world problems. In this paper w ...
Environments with varying reward contingencies constitute a challenge to many living creatures. In such conditions, animals capable of adaptation and learning derive an advantage. Recent studies suggest that neuromodulatory dynamics are a key factor in reg ...
