Abstract
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Incompleteness and Uncertainty: A Major Challenge for Sensory-Motor Systems
We assume that both living creatures and robots must face the same fundamental difficulty: incompleteness (and its direct consequence uncertainty).
Any model of a real phenomenon is incomplete: there are always some hidden variables, not taken into account in the model, that influence the phenomenon. The effect of these hidden variables is that the model and the phenomenon never behave exactly alike. Both living organisms and robotic systems must face this central difficulty: how to use an incomplete model of their environment to perceive, infer, decide and act efficiently.
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Bessière, P. (2008). Probability as an Alternative to Logic for Rational Sensory–Motor Reasoning and Decision. In: Bessière, P., Laugier, C., Siegwart, R. (eds) Probabilistic Reasoning and Decision Making in Sensory-Motor Systems. Springer Tracts in Advanced Robotics, vol 46. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-79007-5_1
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