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The memorization of in-line sensorimotor invariants: toward behavioral ontogeny and enactive agents

机译：在线感觉运动不变量的记忆：针对行为本体论和活性剂

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This paper presents a behavioral ontogeny for artificial agents based on the interactive memorization of sensorimotor invariants. The agents are controlled by continuous timed recurrent neural networks (CTRNNs) which bind their sensors and motors within a dynamic system. The behavioral ontogenesis is based on a phylo-genetic approach: memorization occurs during the agent's lifetime and an evolutionary algorithm discovers CTRNN parameters. This shows that sensorimotor invariants can be durably modified through interaction with a guiding agent. After this phase has finished, agents are able to adopt new sensorimotor invariants relative to the environment with no further guidance. We obtained these kinds of behaviors for CTRNNs with 3-6 units, and this paper examines the functioning of those CTRNNs. For instance, they are able to internally simulate guidance when it is externally absent, in line with theories of simulation in neuroscience and the enactive field of cognitive science.
机译：本文提出了基于感觉运动不变量的交互记忆的人工行为学本体。代理由连续定时递归神经网络（CTRNN）控制，该神经网络将其传感器和电机绑定在动态系统中。行为本体论是基于系统进化论的：记忆发生在代理人的一生中，并且进化算法发现了CTRNN参数。这表明感觉运动不变量可以通过与引导剂的相互作用持久地修饰。此阶段完成后，代理商无需进一步指导即可采用相对于环境的新感觉运动不变量。我们用3-6个单元获得了CTRNN的这类行为，本文研究了这些CTRNN的功能。例如，根据神经科学中的模拟理论和认知科学的活跃领域，他们可以在外部不存在指导时在内部进行模拟。

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