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Computer Science

D-Index
39
Citations
9146
World Ranking
9577
National Ranking
4056

Overview

Richard L. Lewis is affiliated with the University of Michigan-Ann Arbor in the United States. Their research work spans several interconnected fields, primarily in computer science and neuroscience, with significant contributions to cognitive neuroscience and artificial intelligence.

Their research focuses include the study of reinforcement learning in robotics, decision-making and behavioral economics, neural and behavioral psychology studies, psychology of moral and emotional judgment, neural dynamics and brain function, neurobiology of language and bilingualism, and topic modeling.

Richard L. Lewis has published extensively across different academic venues. Frequent publication platforms include:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • Frontiers in Psychology
  • Memory & Cognition
  • Cognitive Research Principles and Implications

Recent notable papers authored or coauthored by Richard L. Lewis feature the following titles and publication venues:

  • Rapid adaptation of predictive models during language comprehension: Aperiodic EEG slope, individual alpha frequency and idea density modulate individual differences in real-time model updating, 2022, Frontiers in Psychology
  • How well do ordinary Americans forecast the growth of COVID-19?, 2022, Memory & Cognition
  • Icon arrays reduce concern over COVID-19 vaccine side effects: a randomized control study, 2022, Cognitive Research Principles and Implications
  • Rational use of episodic and working memory: A normative account of prospective memory, 2020, Neuropsychologia
  • Effects of neural noise on predictive model updating across the adult lifespan, 2022, bioRxiv (Cold Spring Harbor Laboratory)

They have collaborated frequently with several researchers including Tyler J. Adkins, Satinder Singh, Madison Fansher, Poortata Lalwani, and Madelyn Quirk.

Their work emphasizes the understanding of cognitive processes through computational models, neural data analysis, and applications in artificial intelligence, particularly within reinforcement learning and decision-making frameworks.

Best Publications

  • An Activation-Based Model of Sentence Processing as Skilled Memory Retrieval

    Richard L. Lewis;Shravan Vasishth

  • Computational principles of working memory in sentence comprehension.

    Richard L. Lewis;Shravan Vasishth;Julie A. Van Dyke

  • Action-conditional video prediction using deep networks in Atari games

    Junhyuk Oh;Xiaoxiao Guo;Honglak Lee;Richard Lewis

  • Intrinsically Motivated Reinforcement Learning: An Evolutionary Perspective

    Satinder Singh;Richard L Lewis;Andrew G Barto;Jonathan Sorg

  • Deep Learning for Real-Time Atari Game Play Using Offline Monte-Carlo Tree Search Planning

    Xiaoxiao Guo;Satinder Singh;Honglak Lee;Richard L Lewis

  • Interference in short-term memory: the magical number two (or three) in sentence processing.

    Richard L. Lewis

  • Distinguishing effects of structure and decay on attachment and repair: A cue-based parsing account of recovery from misanalyzed ambiguities

    Julie A Van Dyke;Richard L Lewis

  • Argument-Head Distance and Processing Complexity: Explaining both Locality and Antilocality Effects

    Shravan Vasishth;Richard L. Lewis

  • Computational Rationality: Linking Mechanism and Behavior Through Bounded Utility Maximization

    Richard L. Lewis;Andrew Howes;Satinder P. Singh

  • Rational adaptation under task and processing constraints: Implications for testing theories of cognition and action

    Andrew Howes;Richard L. Lewis;Alonso Vera

  • An Architecturally-based Theory of Human Sentence Comprehension

    Richard Lawrence Lewis

  • Processing Polarity: How the Ungrammatical Intrudes on the Grammatical

    Shravan Vasishth;Sven Brüssow;Richard L Lewis;Heiner Drenhaus

  • A computational unification of cognitive behavior and emotion

    Robert P. Marinier;John E. Laird;Richard L. Lewis

  • Short-term forgetting in sentence comprehension: Crosslinguistic evidence from verb-final structures

    Shravan Vasishth;Katja Suckow;Richard L. Lewis;Sabine Kern

  • Where Do Rewards Come From

    Andrew Barto;Richard Lewis;Satinder Singh

  • The dependence of effective planning horizon on model accuracy

    Nan Jiang;Alex Kulesza;Satinder Singh;Richard Lewis

  • Dual-route processing of complex words: new fMRI evidence from derivational suffixation.

    Jennifer Vannest;Thad A. Polk;Richard L. Lewis

  • Retrieval Interference in Syntactic Processing: The Case of Reflexive Binding in English.

    Umesh Patil;Umesh Patil;Shravan Vasishth;Richard L. Lewis

  • Internal Rewards Mitigate Agent Boundedness

    Jonathan Sorg;Satinder P. Singh;Richard L. Lewis

  • Falsifying serial and parallel parsing models: empirical conundrums and an overlooked paradigm.

    Richard L. Lewis

  • Reanalysis and Limited Repair Parsing: Leaping off the Garden Path

    Richard L. Lewis

  • Reward Design via Online Gradient Ascent

    Jonathan Sorg;Richard L Lewis;Satinder P. Singh

Frequent Co-Authors

Satinder Singh
Satinder Singh DeepMind (United Kingdom)
Shravan Vasishth
Shravan Vasishth University of Potsdam
Thad A. Polk
Thad A. Polk University of Michigan–Ann Arbor
Honglak Lee
Honglak Lee University of Michigan–Ann Arbor
John Jonides
John Jonides University of Michigan–Ann Arbor
Allen Newell
Allen Newell Carnegie Mellon University
Marc G. Berman
Marc G. Berman University of Chicago
John E. Laird
John E. Laird University of Michigan–Ann Arbor
Andrew G. Barto
Andrew G. Barto University of Massachusetts Amherst
Roger W. Remington
Roger W. Remington University of Minnesota

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