Kavosh Asadi

EducationPresent Ph.D. in Computer Science, Brown University

Supervisor: Michael L. Littman2015 M.Sc. in Computer Science, University of Alberta

Supervisor: Richard S. Sutton2013 B.E. in Computer Engineering, University of Tehran

Publications2020 Kavosh Asadi, Ronald E. Parr, George D. Konidaris, Michael L. Littman, "Deep RBF

Value Functions for Continuous Control", Arxiv Submission2020 Erwan Lecarpentier, David Abel, Kavosh Asadi, Yuu Jinnai, Emanuel Rachelson, Michael

L. Littman, "Lipschitz Lifelong Reinforcement Learning", Arxiv Submission2019 Seungchan Kim, Kavosh Asadi, George D. Konidaris, Michael L. Littman, "DeepMellow:

Removing the Need for a Target Network in Deep Q-Learning", In 28th International JointConference on Artificial Intelligence

2019 David Abel, Dilip Arumugum, Kavosh Asadi, Yuu Jinnai, Michael L. Littman, Lawson L.S. Wong, "State Abstraction as Compression in Apprenticeship Learning", In 33rd AAAIConference on Artificial Intelligence

2018 Kavosh Asadi, Evan Cater, Dipendra Misra, Michael L. Littman, “Towards a SimpleApproach to Multi-step Model-based Reinforcement Learning", In Neurips Workshop onDeep Reinforcement Learning

2018 Kavosh Asadi, Evan Cater, Dipendra Misra, Michael L. Littman, “Equivalence BetweenWasserstein and Value-Aware Model-based Reinforcement Learning", In ICML Workshopon Prediction and Generative Modeling in Reinforcement Learning

2018 Kavosh Asadi, Dipendra Misra, Michael L. Littman, “Lipschitz Continuity in Model-basedReinforcement Learning", In 35th International Conference on Machine Learning (ICML)

2017 Kavosh Asadi, Cameron Allen, Melrose Roderick, Abdel-rahman Mohamed, George D.Konidaris, Michael L. Littman “Mean Actor Critic", Arxiv Submission

2017 Jason D. Williams, Kavosh Asadi, Geoff Zweig, “Hybrid Code Networks: practical andefficient end-to-end dialog control with supervised and reinforcement learning", In the 55thAnnual Meeting of the Association for Computational Linguistics (ACL)

2017 Kavosh Asadi, Michael L. Littman, “An Alternative Softmax Operator for ReinforcementLearning", In the 34th International Conference on Machine Learning (ICML)

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2016 Kavosh Asadi, Jason D. Williams, “Sample-efficient Deep Reinforcement Learning forDialog Control", Arxiv Submission

2015 Kavosh Asadi, “Strengths, Weakness, and Combinations of Model-based and Model-freeReinforcement Learning”, M.Sc. thesis, University of Alberta

2015 Joseph Modayil, Kavosh Asadi, Richard S. Sutton, “Combining Approximate Planningand Learning in a Cascade”, In the 2nd Multidisciplinary Conference in ReinforcementLearning and Decision Making (RLDM)

Internships2016 & 2017 Microsoft Research Summer Internship at Redmond. Mentor: Jason D. Williams

Teaching2015 University of Alberta, CMPUT 609, TA for Professor Richard S. Sutton

Academic Service2018-2020 Reviewer for International Conference of Machine Learning (ICML)2018-2020 Reviewer for Advances in Neural Information Processing Systems (NeurIPS)

2018 Reviewer for Journal of Machine Learning Research (JMLR) and Journal of ArtificialIntelligence (JAIR)

2016 International Student Advocate of Graduate Student Council, Brown University

Graduate CoursesBrown University

2017 Computer Vision with James Tompkin (4/4)2016 Optimization Methods in Finance with Matteo Riondato (4/4)2016 Advanced Probabilistic Methods with Eli Upfal (4/4)2015 Learning and Sequential Decision Making with Michael Littman (4/4)

University of Alberta2014 Individual study on Reinforcement Learning with Michael Bowling, (4/4)2014 Representation Learning with Dale Schuurmans, (3.7/4)2013 Reinforcement Learning with Richard Sutton, (4/4)2013 Machine Learning with Russell Greiner, (4/4)

Interests{ hiking, rock climbing, & bowling { playing FIFA

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