title: Using reinforcement learning to examine dynamic attention allocation during reading.
abstract: 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.
authors: Department of Psychology, Sun Yat-Sen University.
authors: Yanping
authors: Y
authors: Liu
authors: Erik D
authors: ED
authors: Reichle
authors: Ding-Guo
authors: DG
authors: Gao
mesh_terms: D001288:Attention; D003198:Computer Simulation; D005133:Eye Movements; D011930:Reaction Time; D011932:Reading; D012054:Reinforcement, Psychology
keywords: Attention; Eye movements; Neural networks; Reading; Reinforcement learning