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Daniel Kudenko
Also published under:D. Kudenko
Affiliation
Institute of Data Science, Leibniz University of Hanover, Hanover, Germany
Topic
Neural Network,Deep Learning,Deep Reinforcement Learning,Gated Recurrent Unit,Multi-agent Systems,Square Grid,Advances In Recent Years,Adversarial Domain Adaptation,Artificial Limb,Average Speed,Body Parts,Center Of Mass,Collision,Continuous Action,Continuous Action Space,Continuous Gesture Recognition,Continuous Recognition,Convolutional Layers,Critic Network,Crowded Spaces,Current Graph,Current Observations,Cycle Time,Deep Q-network,Deep Reinforcement Learning Techniques,Domain Adaptation,Domain Adaptation Techniques,Dynamic Obstacles,Edge Weights,End Of Each Iteration,End-users,Environmental Behavior,Filters In Layer,Finger Movements,Gaussian Process,Gesture Recognition,Goal Position,Graph Generation,Grid Cells,Hand Gesture Recognition,Hidden State,Hours Of Training,Human Crowding,Human Movement,Humanoid Robot,Inverse Distance,Leap Motion,Low-pass,Machine Learning,Manufacturing Process,
Biography
Daniel Kudenko received the Ph.D. degree in machine learning from Rutgers—The State University of New Jersey, New Brunswick, in 1998
Currently, he is a Lecturer in Computer Science at the University of York, York, U.K. His research areas are AI for interactive entertainment, machine learning (specifically reinforcement learning), user modeling, and multiagent systems. In many of these areas, he has collaborated with industrial partners in the entertainment and military sector, and has been involved in projects for Eidos, QinetiQ, as well as the Ministry of Defense. He has been leading a research group in York on AI for games and interactive entertainment that works on topics ranging from interactive drama for entertainment and education to football commentary generation. He has participated in several research projects at the University of York, Rutgers University, AT&T Laboratories, and the German Research Center for AI (DFKI) on various topics in artificial intelligence. His work has been published in more than 70 peer-reviewed papers. He coedited three Springer Lecture Notes in Computer Science volumes.
Dr. Kudenko has served on multiple program committees and has been chairing a number of workshops.
Currently, he is a Lecturer in Computer Science at the University of York, York, U.K. His research areas are AI for interactive entertainment, machine learning (specifically reinforcement learning), user modeling, and multiagent systems. In many of these areas, he has collaborated with industrial partners in the entertainment and military sector, and has been involved in projects for Eidos, QinetiQ, as well as the Ministry of Defense. He has been leading a research group in York on AI for games and interactive entertainment that works on topics ranging from interactive drama for entertainment and education to football commentary generation. He has participated in several research projects at the University of York, Rutgers University, AT&T Laboratories, and the German Research Center for AI (DFKI) on various topics in artificial intelligence. His work has been published in more than 70 peer-reviewed papers. He coedited three Springer Lecture Notes in Computer Science volumes.
Dr. Kudenko has served on multiple program committees and has been chairing a number of workshops.