The pattern theory of self in artificial general intelligence: A theoretical framework for modeling self in biologically inspired cognitive architectures

Kevin Ryan, Pulin Agrawal, Stan Franklin

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

In an attempt to provide a unified account for a vast literature discussing a multiplicity of selves, Gallagher (2013) has proposed a pattern theory of self. Subsequent discussion on this account has led to a concern that the pattern theory, as originally presented, stands as a mere list of aspects that fails to explain how they are related in real-time. We suggest that one way to address these criticisms, and further develop the pattern theory of self is by exploring how it can be used to aid research on self in artificial general intelligence, especially in the context of biologically inspired cognitive architectures. We furthermore propose a conceptual implementation for actualizing such research in regards to the LIDA (Learning Intelligent Decision Agent) cognitive model.

Original languageEnglish (US)
Pages (from-to)44-56
Number of pages13
JournalCognitive Systems Research
Volume62
DOIs
StatePublished - Aug 2020

All Science Journal Classification (ASJC) codes

  • Experimental and Cognitive Psychology
  • Cognitive Neuroscience
  • Artificial Intelligence

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