Abstract / Description of output

An open question regarding how people develop their models of the world is how new candidates are generated for consideration out of infinitely many possibilities. We discuss the role that evolutionary mechanisms play in this process. Specifically, we argue that when it comes to developing a global world model, innovation is necessarily incremental, involving the generation and selection among random local mutations and recombinations of (parts of) one's current model. We argue that, by narrowing and guiding exploration, this feature of cognitive search is what allows human learners to discover better theories, without ever grappling directly with the problem of finding a “global optimum,” or best possible world model. We suggest this aspect of cognitive processing works analogously to how blind variation and selection mechanisms drive biological evolution. We propose algorithms developed for program synthesis provide candidate mechanisms for how human minds might achieve this. We discuss objections and implications of this perspective, finally suggesting that a better process-level understanding of how humans incrementally explore compositional theory spaces can shed light on how we think, and provide explanatory traction on fundamental cognitive biases, including anchoring, probability matching, and confirmation bias.
Original languageEnglish
JournalTopics in Cognitive Science
Early online date18 Oct 2023
Publication statusE-pub ahead of print - 18 Oct 2023

Keywords / Materials (for Non-textual outputs)

  • learning
  • inference
  • concepts
  • search
  • evolution
  • approximation
  • MCMC
  • bootstrapping
  • adaptor grammar


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