Liviu Panait

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Theoretical Convergence Guarantees for Cooperative Coevolutionary Algorithms

Liviu Panait, Liviu Panait, 2010, Evolutionary Computation.

Fighting Bloat with Nonparametric Parsimony Pressure

Sean Luke, Liviu Panait, S. Luke, 2002, PPSN.

MASON : A Multi-Agent Simulation Environment

Sean Luke, Keith Sullivan, Claudio Cioffi-Revilla, 2008 .

Cooperative Multi-Agent Learning: The State of the Art

Sean Luke, Liviu Panait, S. Luke, 2005, Autonomous Agents and Multi-Agent Systems.

Ant Foraging Revisited

S. Luke, Liviu Panait, 2004 .

A Visual Demonstration of Convergence Properties of Cooperative Coevolution

R. Paul Wiegand, Sean Luke, Liviu Panait, 2004, PPSN.

Biasing Coevolutionary Search for Optimal

S. Luke, R. P. Wiegand, Liviu Panait, 2006 .

Collaborative Multiagent Learning : A Survey

S. Luke, Liviu Panait, 2003 .

Theoretical Advantages of Lenient Learners in Multiagent Systems

Karl Tuyls, Liviu Panait, K. Tuyls, 2007 .

A Comparative Study of Two Competitive Fitness Functions

Liviu Panait, 2002 .

Learning to Generate Image Embeddings with User-level Differential Privacy

Maxwell D. Collins, Florian Schroff, Sewoong Oh, 2022, 2211.10844.

The analysis and design of concurrent learning algorithms for cooperative multiagent systems

Sean Luke, Liviu Panait, S. Luke, 2007 .

Can good learners always compensate for poor learners?

Sean Luke, Keith Sullivan, Liviu Panait, 2006, AAMAS '06.

The Analysis and Design of Concurrent Learning Algorithms for Cooperative

Sean Luke, Liviu Panait, S. Luke, 2006 .

An Overview of Cooperative and Competitive Multiagent Learning

Karl Tuyls, Sean Luke, Han La Poutré, 2005, LAMAS.

Is The Perfect The Enemy Of The Good?

Sean Luke, Liviu Panait, S. Luke, 2002, GECCO.

Lexicographic Parsimony Pressure

Sean Luke, Liviu Panait, S. Luke, 2002, GECCO.

Methods for Evolving Robust Programs

Sean Luke, Liviu Panait, S. Luke, 2003, GECCO.

Tunably decentralized algorithms for cooperative target observation

Sean Luke, Keith Sullivan, Liviu Panait, 2005, AAMAS '05.

Theoretical Advantages of Lenient Learners: An Evolutionary Game Theoretic Perspective

Karl Tuyls, Sean Luke, Liviu Panait, 2008, J. Mach. Learn. Res..

Theoretical advantages of lenient Q-learners: an evolutionary game theoretic perspective

Karl Tuyls, Liviu Panait, K. Tuyls, 2007, AAMAS '07.

MASON: A Multiagent Simulation Environment

Sean Luke, Keith Sullivan, Claudio Cioffi-Revilla, 2005, Simul..

Population Implosion in Genetic Programming

Sean Luke, Liviu Panait, Gabriel Catalin Balan, 2003, GECCO.

Selecting informative actions improves cooperative multiagent learning

Sean Luke, Liviu Panait, S. Luke, 2006, AAMAS '06.

Biasing Coevolutionary Search for Optimal Multiagent Behaviors

R. Paul Wiegand, Sean Luke, Liviu Panait, 2006, IEEE Transactions on Evolutionary Computation.

The Development of the AQ20 Learning System and Initial Experiments

Ryszard S. Michalski, Guido Cervone, Liviu Panait, 2001, Intelligent Information Systems.

Nutrition5k: Towards Automatic Nutritional Understanding of Generic Food

Tobias Weyand, Liviu Panait, Jack Sim, 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Combining Machine Learning with Evolutionary Computation: Recent Results on LEM

Kenneth A. Kaufman, Ryszard S. Michalski, Guido Cervone, 2000 .

A Comparison of Bloat Control Methods for Genetic Programming

Sean Luke, Liviu Panait, S. Luke, 2006, Evolutionary Computation.

Learning to Generate Image Embeddings with User-Level Differential Privacy

Maxwell D. Collins, Florian Schroff, Sewoong Oh, 2022, 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

A Sensitivity Analysis of a Cooperative Coevolutionary Algorithm Biased for Optimization

R. Paul Wiegand, Sean Luke, Liviu Panait, 2004, GECCO.

Alternative Bloat Control Methods

Sean Luke, Liviu Panait, S. Luke, 2004, GECCO.

Lenient learners in cooperative multiagent systems

Sean Luke, Keith Sullivan, Liviu Panait, 2006, AAMAS '06.

An Analysis of Cooperative Coevolutionary Algorithms A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at George Mason University

Jeffrey K. Bassett, Kenneth D. De Jong, K. A. Jong, 2003 .

Improving coevolutionary search for optimal multiagent behaviors

S. Luke, R. P. Wiegand, Liviu Panait, 2003, IJCAI 2003.

A Comparison Of Two Competitive Fitness Functions

Sean Luke, Liviu Panait, S. Luke, 2002, GECCO.

A survey and comparison of tree generation algorithms

Sean Luke, Liviu Panait, S. Luke, 2001 .

Is The Perfect The Enemy Of The Good?

S. Luke, Liviu Panait, 2002, GECCO.

MASON: A New Multi-Agent Simulation Toolkit

Sean Luke, Keith Sullivan, Claudio Cioffi-Revilla, 2004 .

A pheromone-based utility model for collaborative foraging

Sean Luke, Liviu Panait, S. Luke, 2004, Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems, 2004. AAMAS 2004..

Lenience towards Teammates Helps in Cooperative Multiagent Learning

Sean Luke, Keith Sullivan, Liviu Panait, 2005 .

Learning Ant Foraging Behaviors

Sean Luke, Liviu Panait, S. Luke, 2004 .