2016
DOI: 10.1155/2016/4296356
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Abstract: Associative learning, including classical conditioning and operant conditioning, is regarded as the most fundamental type of learning for animals and human beings. Many models have been proposed surrounding classical conditioning or operant conditioning. However, a unified and integrated model to explain the two types of conditioning is much less studied. Here, a model based on neuromodulated synaptic plasticity is presented. The model is bioinspired including multistored memory module and simulated VTA dopami… Show more

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Cited by 7 publications
(5 citation statements)
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“…Therefore, two cameras located in the center of the navigation environment are set up. The cameras are Mercury MER-040-60UC The kinematic model [30] of the robotic fish is approximated by a polynomial and sinusoidal synthesis, as shown in formula (27).…”
Section: Physical Experimentsmentioning
confidence: 99%
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“…Therefore, two cameras located in the center of the navigation environment are set up. The cameras are Mercury MER-040-60UC The kinematic model [30] of the robotic fish is approximated by a polynomial and sinusoidal synthesis, as shown in formula (27).…”
Section: Physical Experimentsmentioning
confidence: 99%
“…Moreover, Touretzky et al have further developed the computational model of Skinner's OCR theory [18]. Later, many scholars have carried out extensive research on the computational model of operational conditioned reflexes [19][20][21][22][23][24][25][26][27][28][29][30][31][32]. Robots are showing more self-learning ability and self-adaptability, similar to organisms.…”
Section: Introductionmentioning
confidence: 99%
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“…Other studies show that promoting the evolution of modular neural networks by introducing a cost for neural connections can mitigate catastrophic forgetting and improve learning-which is regulated with neuromodulation [13]. Neuromodulation has also been used to develop conflict learning in ANNs [16] and associative learning in robots [20]; these two approaches employ neuromodulation but do not use neuroevolution as a learning mechanism. These approaches modulate learning, resulting in developmental plasticity, by regulating the local learning rate of neurons in the network; they do not, however, demonstrate how behaviour can be regulated in a short-term, reversible way without affecting learning to facilitate immediate behavioural changes.…”
Section: Achieving Developmental Plasticity With Neuromodulationmentioning
confidence: 99%