Multiagent Pathfinding Professors in Global

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Jamal Bentahar
Concordia University Canada
multi-agent systems
multi-agent interaction
security in multi-agent systems
agent-based software engineering
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Guni Sharon
Texas A&M University United States of America
multiagent pathfinding
multiagent modeling simulation
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Zinovi Rabinovich
Carleton University Canada
multi-agent learning
multi-agent systems
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Maria Polukarov
King's College London United Kingdom
multi-agent systems
multi-agent reinforcement learning
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Nicoletta Fornara
Università della Svizzera italiana Switzerland
multiagent systems
normative multiagent systems
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David Parkes
Harvard University United States of America
multi-agent ai
multi-agent reinforcement learning
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Vahid Yazdanpanah
University of Southampton United Kingdom
multiagent systems
agent-based computing
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Mithun Chakraborty
New York University United States of America
multiagent systems
agent-based modeling
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Brandon Haworth
University of Victoria Canada
multi-agent reinforcement learning
agent-based modelling
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Sita Syal
University of Michigan United States of America
agent-based modeling
multi-attribute decision making
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Bouchra Nasri
University of Montreal Canada
multilevel analysis
multivariate analysis
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Yuehua Wu
York University Canada
multivariate analysis
multiple change-point analysis
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Manuel Lopez-ibanez
University of Manchester United Kingdom
multi-objective optimisation
multi-criteria decision making
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Olaf Schenk
Università della Svizzera italiana Switzerland
multicore algorithms
manycore algorithms
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Daniel Harabor
Monash University Australia
multi-agent pathfinding
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Minghui Zhu
Pennsylvania State University United States of America
multi-agent networks
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Michael Bowling
University of Alberta Canada
multiagent learning
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Manxi Wu
University of California, Berkeley United States of America
multi-agent learning
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Sindri Magnússon
Stockholm University Sweden
multi-agent learning
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Eugene Vinitsky
New York University Tandon School of Engineering United States of America
multi-agent learning
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Jakob Foerster
University of Oxford United Kingdom
multi-agent learning
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