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Computer Science

D-Index
38
Citations
5905
World Ranking
10262
National Ranking
4307

Overview

David V. Pynadath is a researcher affiliated with the University of Southern California in the United States. Their work spans multiple fields including Psychology, Social Sciences, and Computer Science, with significant contributions in subfields such as Social Psychology, Safety Research, Cognitive Neuroscience, Artificial Intelligence, and General Decision Sciences.

The scientist's research focuses on a variety of topics, notably Human-Automation Interaction and Safety, Ethics and Social Impacts of AI, Psychology of Moral and Emotional Judgment, Decision-Making and Behavioral Economics, Evacuation and Crowd Dynamics, Child and Animal Learning Development, and Explainable Artificial Intelligence (XAI).

Pynadath has published research in several venues, including arXiv (Cornell University), the 2022 31st IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), Computational and Mathematical Organization Theory, Developments in the Built Environment, and the Proceedings of the AAAI Conference on Artificial Intelligence.

Some recent papers authored or co-authored by David V. Pynadath include:

  • Disaster world, 2022, Computational and Mathematical Organization Theory
  • Explainable Reinforcement Learning in Human-Robot Teams: The Impact of Decision-Tree Explanations on Transparency, 2022, 2022 31st IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)

Frequent co-authors collaborating with Pynadath are:

  • Nikolos Gurney
  • Volkan Ustun
  • John H. Miller
  • Ning Wang
  • Stacy Marsella

Best Publications

  • The communicative multiagent team decision problem: analyzing teamwork theories and models

    David V. Pynadath;Milind Tambe

  • Taming decentralized POMDPs: towards efficient policy computation for multiagent settings

    R. Nair;M. Tambe;M. Yokoo;D. Pynadath

  • Plan, Activity, and Intent Recognition: Theory and Practice

    Gita Sukthankar;Christopher Geib;Hung Hai Bui;David Pynadath

  • Monitoring teams by overhearing: a multi-agent plan-recognition approach

    Gal A. Kaminka;David V. Pynadath;Milind Tambe

  • Towards adjustable autonomy for the real world

    Paul Scerri;David V. Pynadath;Milind Tambe

  • PsychSim: modeling theory of mind with decision-theoretic agents

    David V. Pynadath;Stacy C. Marsella

  • PsychSim: Agent-based Modeling of Social Interactions and Influence.

    David V. Pynadath

  • BiLAT: A Game-Based Environment for Practicing Negotiation in a Cultural Context

    Julia M. Kim;Randall W. Hill;Paula J. Durlach;H. Chad Lane

  • Multiagent teamwork: analyzing the optimality and complexity of key theories and models

    David V. Pynadath;Milind Tambe

  • A prototype infrastructure for distributed robot-agent-person teams

    Paul Scerri;David Pynadath;Lewis Johnson;Paul Rosenbloom

  • Probabilistic State-Dependent Grammars for Plan Recognition

    David V. Pynadath;Michael P. Wellman

  • An Automated Teamwork Infrastructure for Heterogeneous Software Agents and Humans

    David V. Pynadath;Milind Tambe

  • Electric Elves: Applying Agent Technology to Support Human Organizations

    Hans Chalupsky;Yolanda Gil;Craig A. Knoblock;Kristina Lerman

  • Toward team-oriented programming

    D. V. Pynadath;M. Tambe;N. Chauvat;L. Cavedon

  • Trust Calibration within a Human-Robot Team: Comparing Automatically Generated Explanations

    Ning Wang;David V. Pynadath;Susan G. Hill

  • Accounting for context in plan recognition, with application to traffic monitoring

    David V. Pynadath;Michael P. Wellman

  • Thespian: using multi-agent fitting to craft interactive drama

    Mei Si;Stacy C. Marsella;David V. Pynadath

  • ELECTRIC ELVES Agent Technology for Supporting Human Organizations

    Hans Chalupsky;Yolanda Gil;Craig A. Knoblock;Kristina Lerman

  • Adjustable autonomy in real-world multi-agent environments

    Paul Scerri;David Pynadath;Milind Tambe

  • Adaptive agent integration architectures for heterogeneous team members

    M. Tambe;D.V. Pynadath;N. Chauvat;A. Das

Frequent Co-Authors

Milind Tambe
Milind Tambe Harvard University
Stacy Marsella
Stacy Marsella Northeastern University
Gal A. Kaminka
Gal A. Kaminka Bar-Ilan University
Michael P. Wellman
Michael P. Wellman University of Michigan–Ann Arbor
Paul S. Rosenbloom
Paul S. Rosenbloom University of Southern California
Craig A. Knoblock
Craig A. Knoblock University of Southern California
Yolanda Gil
Yolanda Gil University of Southern California
Kristina Lerman
Kristina Lerman University of Southern California
Bamshad Mobasher
Bamshad Mobasher DePaul University
Louis-Philippe Morency
Louis-Philippe Morency Carnegie Mellon University

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