The leabra cognitive architecture: how to play 20 principles with nature and win!. O'Reilly, R., Hazy, T., & Herd, S. The Oxford Handbook of Cognitive Science, 2012. ![The leabra cognitive architecture: how to play 20 principles with nature and win! [pdf]](https://bibbase.org/img/filetypes/pdf.svg "pdf")
Paper Website abstract bibtex This chapter provides a synthetic review of a long-term effort to produce an internally consistent theory of the neural basis of human cognition, the Leabra cognitive architecture, which explains a great deal of brain and behavioral data. In a highly influential commentary, Allen Newell (1973) first issued a call for a more comprehensive, principled approach to studying cognition. “You can’t play 20 questions with nature, and win,” he said, alluding to the old parlor guessing game involving 20 yes or no questions. His point was that cognition, and the brain that gives rise to it, is just too complex and multidimensional a system to ever hope that a series of narrowly framed experiments and/or models would ever be able to characterize it. Instead, a single cognitive architecture should be used to simulate a wide range of data at many levels in a cumulative manner. However, these cognitive architectures tend to be complex and difficult to fully comprehend. In an attempt to most clearly and simply present the Leabra biologically- based cognitive architecture, we articulate 20 principles that motivate its design, at multiple levels of analysis.
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abstract = {This chapter provides a synthetic review of a long-term effort to produce an internally consistent theory of the neural basis of human cognition, the Leabra cognitive architecture, which explains a great deal of brain and behavioral data. In a highly influential commentary, Allen Newell (1973) first issued a call for a more comprehensive, principled approach to studying cognition. “You can’t play 20 questions with nature, and win,” he said, alluding to the old parlor guessing game involving 20 yes or no questions. His point was that cognition, and the brain that gives rise to it, is just too complex and multidimensional a system to ever hope that a series of narrowly framed experiments and/or models would ever be able to characterize it. Instead, a single cognitive architecture should be used to simulate a wide range of data at many levels in a cumulative manner. However, these cognitive architectures tend to be complex and difficult to fully comprehend. In an attempt to most clearly and simply present the Leabra biologically- based cognitive architecture, we articulate 20 principles that motivate its design, at multiple levels of analysis.},
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