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Extending sensorimotor contingency theory: prediction, planning, and action generation

机译：扩展感觉运动应急理论：预测，计划和行动产生

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One of the main assertions of sensorimotor contingency theory is that sensory experience is not generated by activating an internal representation of the outside world through sensory signals, but corresponds to a mode of exploration and hence is an active process. Perception and sensory awareness emerge from using the structure of changes in the sensory input resulting from these exploratory actions, called sensorimotor contingencies (SMCs), for planning, reasoning, and goal achievement. Using a previously developed computational model of SMCs we show how an artificial agent can plan ahead with SMCs and use them for action guidance. Our main assumption is that SMCs are associated with a utility for the agent, and that the agent selects actions that maximize this utility. We analyze the properties of the resulting actions in a robot that is endowed with several sensory modalities and controlled by our model in a simple environment. The results demonstrate that its actions avoid aversive events, and that it can achieve a low-level form of spatial awareness that is resilient to the complete loss of a sensory modality.
机译：感觉运动权变理论的主要主张之一是感觉体验不是通过感觉信号激活外部世界的内部表示而产生的，而是对应于一种探索模式，因此是一个活跃的过程。感知和感官意识是通过使用这些探索性动作（称为感觉运动意外事件（SMC））所产生的感觉输入变化的结构来进行计划，推理和达成目标而出现的。使用先前开发的SMC计算模型，我们展示了人工代理如何与SMC预先计划并将其用于行动指导。我们的主要假设是SMC与该代理的实用程序相关联，并且该代理选择使该实用程序最大化的操作。我们在具有简单感官环境并具有模型控制功能的机器人中分析了所产生动作的属性。结果表明，它的行为避免了厌恶事件，并且它可以实现一种低层形式的空间意识，可以抵御感觉模态的完全丧失。

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