Heuristics: intelligent search strategies for computer problem solving
Heuristics: intelligent search strategies for computer problem solving
Artificial Intelligence
Proceedings of the first international conference on Principles of knowledge representation and reasoning
Rigid Flexibility: The Logic of Intelligence (Applied Logic Series)
Rigid Flexibility: The Logic of Intelligence (Applied Logic Series)
A comprehensive analysis of hyper-heuristics
Intelligent Data Analysis
On attention mechanisms for AGI architectures: a design proposal
AGI'12 Proceedings of the 5th international conference on Artificial General Intelligence
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In this paper we consider the issue of endowing an AGI system with decision-making capabilities for operation in real-world environments or those of comparable complexity. While action-selection is a critical function of any AGI system operating in the real-world, very few applicable theories or methodologies exist to support such functionality, when all necessary factors are taken into account. Decision theory and standard search techniques require several debilitating simplifications, including determinism, discrete state spaces, exhaustive evaluation of all possible future actions and a coarse grained representation of time. Due to the stochastic and continuous nature of real-world environments and inherent time-constraints, direct application of decision-making methodologies from traditional decision theory and search is not a viable option. We present predictive heuristics as a way to bridge the gap between the simplifications of decision theory and search, and the complexity of real-world environments.