Emergence of coherent behaviors from homogenous sensorimotor coupling

S. Bovet, R. Pfeifer
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引用次数: 19

Abstract

It seems self-evident that an agent's perception of its surrounding environment is tightly coupled to its behavior. However, most robot control architectures make some assumptions about how sensory information relates to motor actions, in order to provide a set of basic behaviors (such as reflexes). It is largely unknown to what extent these biases reduce the potential for the generation of diverse or unexpected behaviors from the agent-environment interaction. In this paper, we propose a new model of robot control architecture, consisting of homogeneous, non-hierarchical coupling, which only learns the correlation of simultaneous activity between any pair of sensor or motor modalities. We show that the propagation of activity across the different modalities, modulated by the learnt correlations, can lead to the emergence of coherent complex behaviors, such as approaching and following an object, or solving a task based on the temporal relationship between an early clue and a delayed reward
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同质感觉运动耦合中相干行为的出现
似乎不言自明的是,一个主体对周围环境的感知与它的行为是紧密相连的。然而,为了提供一组基本行为(如反射),大多数机器人控制架构都对感觉信息与运动动作之间的关系做出了一些假设。这些偏差在多大程度上减少了从代理-环境相互作用中产生多样化或意外行为的可能性,这在很大程度上是未知的。在本文中,我们提出了一种新的机器人控制体系结构模型,它由同构的、非分层的耦合组成,它只学习任意一对传感器或运动模态之间同时活动的相关性。我们发现,在不同模式的活动传播中,由习得的相关性调节,可以导致连贯复杂行为的出现,比如接近和跟随一个物体,或者基于早期线索和延迟奖励之间的时间关系解决一个任务
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