Richard Dearden
About
Richard Dearden has authored 35 papers that have received a total of 1.3k indexed citations.
This includes 27 papers in Artificial Intelligence, 9 papers in Control and Systems Engineering and 5 papers in Computer Vision and Pattern Recognition. The topics of these papers are AI-based Problem Solving and Planning (17 papers), Bayesian Modeling and Causal Inference (9 papers) and Reinforcement Learning in Robotics (9 papers). Richard Dearden is often cited by papers focused on AI-based Problem Solving and Planning (17 papers), Bayesian Modeling and Causal Inference (9 papers) and Reinforcement Learning in Robotics (9 papers) and collaborates with scholars based in United Kingdom, United States and Canada. Richard Dearden's co-authors include Craig Boutilier, Nicolas Meuleau, Jeremy Wyatt, Rich Washington and Sailesh Ramakrishnan and has published in prestigious journals such as Journal of Neuroscience, Proceedings of the IEEE and Artificial Intelligence.
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