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The Effects of Bounding Rationality on the Performance and Learning of CHREST Agents in Tileworld
[chapter]
2014
Research and Development in Intelligent Systems XXXI
Learning in complex and complicated domains is fundamental to performing suitable and timely actions within them. The ability of chess masters to learn and recall huge numbers of board configurations to produce near-optimal actions provides evidence that chunking mechanisms are likely to underpin human learning. Cognitive theories based on chunking argue in favour for the notion of bounded rationality since relatively small chunks of information are learnt in comparison to the total information
doi:10.1007/978-3-319-12069-0_10
dblp:conf/sgai/Lloyd-KellyLG14
fatcat:li43qnkqcbeoncimsn27svlr3q