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spacetime is necessary for achieving humanlike AGI using feasible resources. As an argument against the necessity of this sort of prior knowledge, Ben Kuipers and his colleagues ISNIK 21 have shown that an AI system can learn via experience that its perceptual stream comes from a world with three, rather
ssumption about the nature of the environments that intelligent agents are operating in. As discussed in roe06] it requires an assumption related to Peirce's philosophical axiom of the "tendency to take habits," which posits that in the real world, entities possessing some similar patterns have a proba
urations that carry out sensorimotor and categorization tasks. The emergence of higher-level cognition from this approach seems rather unlikely. • Ben Kuipers and his colleagues INIK07, MKOS, NIKOalhave pursued an extremely innovative research program which combines qualitative reasoning and reinforcement
nowledge representation and learning. Among the many kinds of patterns in intelligent systems, semiotic patterns are particularly interesting ones. Peirce decomposed these into three categories: • iconic patterns, which are patterns of contextually important internal similarity between two entities (e
igurations that carry out sensorimotor and categorization tasks. The emergence of higher-level cognition from this approach seems rather unlikely. e Ben Kuipers and his colleagues [MK07, MIX08, MIXO09]have pursued an extremely innovative research program which combines qualitative reasoning and reinforcement
knowledge representation and learning. Among the many kinds of patterns in intelligent systems, semiotic patterns are particularly interesting ones. Peirce decomposed these into three categories: @ iconic patterns, which are patterns of contextually important internal similarity between two entities (e.
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