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Sven Koenig

Sven Koenig is interested in intelligent systems that operate in large, nondeterministic, nonstationary or only partially known domains. Most of his research centers around techniques for decision making (planning and learning) that enable single situated agents (such as robots or decision-support systems) and teams of agents to act intelligently in their environments and exhibit goal-directed behavior in real time, even if they have only incomplete knowledge of their environments, imperfect abilities to manipulate them, limited or noisy perception or insufficient reasoning speed. He believes that finding good solutions to these problems requires approaches that cut across many different fields and, consequently, his research draws on areas such as artificial intelligence, decision theory, and operations research. Applications of his research include robotics, logistics, and video games.

He is a fellow of the Association for the Advancement of Artificial Intelligence (AAAI), the Association for Computing Machinery (ACM), the Institute of Electrical and Electronics Engineers (IEEE), and the American Association for the Advancement of Science (AAAS).

Education

Ph.D. and M.S., Computer Science, Carnegie Mellon University

M.S., Computer Science, University of California at Berkeley

Diplom, Computer Science and Business Administration, University of Hamburg

Research Areas

View CS Education

CS Education

Developing learning and teaching tools for information and computer sciences.

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