Using reinforcement learning to examine dynamic attention allocation during reading

Yanping Liu, Erik D. Reichle*, Ding Guo Gao

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)


A fundamental question in reading research concerns whether attention is allocated strictly serially, supporting lexical processing of one word at a time, or in parallel, supporting concurrent lexical processing of two or more words (Reichle, Liversedge, Pollatsek, & Rayner, 2009). The origins of this debate are reviewed. We then report three simulations to address this question using artificial reading agents (Liu & Reichle, 2010; Reichle & Laurent, 2006) that learn to dynamically allocate attention to 1-4 words to "read" as efficiently as possible. These simulation results indicate that the agents strongly preferred serial word processing, although they occasionally attended to more than one word concurrently. The reason for this preference is discussed, along with implications for the debate about how humans allocate attention during reading.

Original languageEnglish
Pages (from-to)1507-1540
Number of pages34
JournalCognitive Science
Issue number8
Publication statusPublished - 2013
Externally publishedYes


  • attention
  • eye movements
  • neural networks
  • reading
  • reinforcement learning


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