{"title":"A cognitive architecture theory of anticipatory thinking","authors":"Steven J. Jones, John E. Laird","doi":"10.1002/aaai.12102","DOIUrl":null,"url":null,"abstract":"<p>We theorize that anticipatory thinking (AT) uses the same computational infrastructure as general cognition as described in the Common Model of Cognition. We extend the Common Model with results from research on event cognition. Using these building blocks, we present a five-step process model of AT as realized in cognitive architecture components. We then revisit simplifying assumptions underlying our model and expand our theory in response. Finally, we make predictions that are entailed by our account of AT, focusing on how computational limits in both natural and artificial cognitive systems can impact support for AT.</p>","PeriodicalId":7854,"journal":{"name":"Ai Magazine","volume":"44 2","pages":"155-164"},"PeriodicalIF":2.5000,"publicationDate":"2023-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/aaai.12102","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ai Magazine","FirstCategoryId":"94","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/aaai.12102","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0
Abstract
We theorize that anticipatory thinking (AT) uses the same computational infrastructure as general cognition as described in the Common Model of Cognition. We extend the Common Model with results from research on event cognition. Using these building blocks, we present a five-step process model of AT as realized in cognitive architecture components. We then revisit simplifying assumptions underlying our model and expand our theory in response. Finally, we make predictions that are entailed by our account of AT, focusing on how computational limits in both natural and artificial cognitive systems can impact support for AT.
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AI Magazine publishes original articles that are reasonably self-contained and aimed at a broad spectrum of the AI community. Technical content should be kept to a minimum. In general, the magazine does not publish articles that have been published elsewhere in whole or in part. The magazine welcomes the contribution of articles on the theory and practice of AI as well as general survey articles, tutorial articles on timely topics, conference or symposia or workshop reports, and timely columns on topics of interest to AI scientists.
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