Humans use directed and random exploration to solve the explore-exploit dilemma

Robert C. Wilson, Andra Geana, John M. White, Elliot A. Ludvig, Jonathan D. Cohen

Research output: Contribution to journalArticlepeer-review

320 Scopus citations

Abstract

All adaptive organisms face the fundamental tradeoff between pursuing a known reward (exploitation) and sampling lesser-known options in search of something better (exploration). Theory suggests at least two strategies for solving this dilemma: a directed strategy in which choices are explicitly biased toward information seeking, and a random strategy in which decision noise leads to exploration by chance. In this work we investigated the extent to which humans use these two strategies. In our "Horizon task," participants made explore- exploit decisions in two contexts that differed in the number of choices that they would make in the future (the time horizon). Participants were allowed to make either a single choice in each game (horizon 1), or 6 sequential choices (horizon 6), giving them more opportunity to explore. By modeling the behavior in these two conditions, we were able to measure exploration-related changes in decision making and quantify the contributions of the two strategies to behavior. We found that participants were more information seeking and had higher decision noise with the longer horizon, suggesting that humans use both strategies to solve the exploration- exploitation dilemma. We thus conclude that both information seeking and choice variability can be controlled and put to use in the service of exploration.

Original languageEnglish (US)
Pages (from-to)2074-2081
Number of pages8
JournalJournal of Experimental Psychology: General
Volume143
Issue number6
DOIs
StatePublished - 2014

All Science Journal Classification (ASJC) codes

  • Experimental and Cognitive Psychology
  • Developmental Neuroscience
  • General Psychology

Keywords

  • Decision making
  • Decision noise
  • Explore-exploit
  • Information bonus
  • Reinforcement learning

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