World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
67
Citations
18407
World Ranking
2191
National Ranking
1100

Overview

Jordan Pollack is affiliated with Brandeis University in the United States and conducts research primarily within the field of Computer Science. Their body of work mainly focuses on subfields such as Artificial Intelligence, Biomedical Engineering, Mechanical Engineering, Sociology and Political Science, and Condensed Matter Physics.

The scientist has contributed notably to topics including Evolutionary Algorithms and Applications, Evolutionary Game Theory and Cooperation, Reinforcement Learning in Robotics, Micro and Nano Robotics, Game Theory and Applications, Experimental Behavioral Economics Studies, and Slime Mold and Myxomycetes Research.

Jordan Pollack has published articles in several venues, reflecting the interdisciplinary nature of their research. Frequent publication venues include:

  • arXiv (Cornell University)
  • Proceedings of the Genetic and Evolutionary Computation Conference Companion
  • Current Biology
  • Langmuir
  • Artificial Life

Recent papers authored or coauthored by Jordan Pollack cover a range of topics and publication years, such as:

  • "A unicellular walker controlled by a microtubule-based finite-state machine," 2022, Current Biology
  • "Nanofluid Boiling on Micro/Nano-engineered Surfaces," 2021, Langmuir
  • "Emergent Resource Exchange and Tolerated Theft Behavior Using Multiagent Reinforcement Learning," 2024, Artificial Life
  • "A unicellular walker controlled by a microtubule-based finite state machine," 2022, Biophysical Journal
  • "Issue Information," 2023, AI Magazine

Collaboration is a significant aspect of Pollack's work, with frequent coauthors including Jack Garbus, Ben T. Larson, Wallace F. Marshall, and Thomas Willkens. Jack Garbus appears as a coauthor with multiple joint publications.

Jordan Pollack's academic contributions span multiple domains, with emphases on both theoretical and applied aspects of evolutionary computation, robotics, and interdisciplinary studies bridging social sciences and engineering disciplines.

Best Publications

  • An evolutionary algorithm that constructs recurrent neural networks

    P.J. Angeline;G.M. Saunders;J.B. Pollack

  • Recursive distributed representations

    J. B. Pollack

  • Automatic design and manufacture of robotic lifeforms

    Hod Lipson;Jordan B. Pollack

  • Massively parallel parsing: a strongly interactive model of natural language interpretation

    David L. Waltz;Jordon B. Pollack

  • The induction of dynamical recognizers

    Jordan B. Pollack

  • Backpropagation is Sensitive to Initial Conditions.

    John F. Kolen;Jordan B. Pollack

  • Back Propagation is Sensitive to Initial Conditions

    John F. Kolen;Jordan B. Pollack

  • Competitive Environments Evolve Better Solutions for Complex Tasks

    Peter J. Angeline;Jordan B. Pollack

  • Embodied Evolution: Distributing an evolutionary algorithm in a population of robots

    Richard A. Watson;Sevan G. Ficici;Jordan B. Pollack

  • Creating high-level components with a generative representation for body-brain evolution

    Gregory S. Hornby;Jordan B. Pollack

  • Toward the Evolution of Dynamical Neural Networks for Minimally Cognitive Behavior

    Pattie Maes;Maja J. Mataric;Jean-Arcady Meyer;Jordan Pollack

  • Co-evolution of Pursuit and Evasion II: Simulation Methods and Results

    Pattie Maes;Maja J. Mataric;Jean-Arcady Meyer;Jordan Pollack

  • Co-Evolution in the Successful Learning of Backgammon Strategy

    Jordan B. Pollack;Alan D. Blair

  • Reducing bloat and promoting diversity using multi-objective methods

    Edwin D. de Jong;Richard A. Watson;Jordan B. Pollack

  • Modeling Building-Block Interdependency

    Richard A. Watson;Greg Hornby;Jordan B. Pollack

  • Evolutionary Module Acquisition

    Peter J. Angeline;Jordan Pollack

  • The advantages of generative grammatical encodings for physical design

    G.S. Hornby;J.B. Pollack

  • Coevolutionary dynamics in a minimal substrate

    Richard A. Watson;Jordan B. Pollack

  • Generative representations for the automated design of modular physical robots

    G.S. Hornby;H. Lipson;J.B. Pollack

  • Method and apparatus for distributing information to users

    Jordan Pollack;Shaun Cutts;Andres Rodriguez;Jeremy Stevenson

Frequent Co-Authors

Maja J. Matarić
Maja J. Matarić University of Southern California
Stewart W. Wilson
Stewart W. Wilson University of Illinois at Urbana-Champaign
Hod Lipson
Hod Lipson Columbia University
Phil Husbands
Phil Husbands University of Sussex
Caroline Palmer
Caroline Palmer McGill University
Michael Rosbash
Michael Rosbash Brandeis University
Masahiro Fujita
Masahiro Fujita Sony (Japan)
Jack M. Loomis
Jack M. Loomis University of California, Santa Barbara

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