Ronald Parr
About
Ronald Parr has authored 44 papers that have received a total of 1.6k indexed citations.
This includes 29 papers in Artificial Intelligence, 11 papers in Management Science and Operations Research and 9 papers in Computational Theory and Mathematics. The topics of these papers are Reinforcement Learning in Robotics (22 papers), Machine Learning and Algorithms (8 papers) and Bayesian Modeling and Causal Inference (7 papers). Ronald Parr is often cited by papers focused on Reinforcement Learning in Robotics (22 papers), Machine Learning and Algorithms (8 papers) and Bayesian Modeling and Causal Inference (7 papers) and collaborates with scholars based in United States and France. Ronald Parr's co-authors include Michail G. Lagoudakis, Vincent Conitzer, Daphne Koller, Jason Pazis and Christopher Painter-Wakefield and has published in prestigious journals such as IEEE Transactions on Signal Processing and The International Journal of Robotics Research
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