Computably Continuous Reinforcement-Learning Objectives Are PAC-Learnable - researchr publication authors

researchr

You are not signed in
Sign in
Sign up

Cambridge Yang, Michael L. Littman, Michael Carbin. Computably Continuous Reinforcement-Learning Objectives Are PAC-Learnable. In Brian Williams 0001, Yiling Chen 0001, Jennifer Neville, editors, Thirty-Seventh AAAI Conference on Artificial Intelligence, AAAI 2023, Thirty-Fifth Conference on Innovative Applications of Artificial Intelligence, IAAI 2023, Thirteenth Symposium on Educational Advances in Artificial Intelligence, EAAI 2023, Washington, DC, USA, February 7-14, 2023. pages 10729-10736, AAAI Press, 2023. [doi]

This author has not been identified. Look up 'Cambridge Yang' in GoogleThis author has not been identified. Look up 'Michael L. Littman' in GoogleThis author has not been identified. Look up 'Michael Carbin' in Google

runs on WebDSL