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Barbados Workshop 2023 Bellairs Invitational Workshop on Time, Input, and Action Abstraction in Reinforcement Learning 17-24 March 2023 Program Reading Participants Venue Travel Reinforcement learning has succeeded across a wide range of games such as Atari, Go, chess, Dota, and Starcraft. However, current algorithms struggle with long and complex tasks unless they are guided by expert knowledge, often in the form of frequent intermediate rewards. In contrast, humans achieve distant goals by generating abstract plans and then sticking to them over minutes, days, weeks, and even years and adapting the plans when needed. Despite ever-increasing compute budgets, current algorithms lack this ability because they operate in the space of low-level actions for assigning credit, building models, and planning. What kinds of structure will enable future algorithms to autonomously solve complex tasks with long horizons? What are the best mathematical tools for developing t...
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10 - proceedings.mlr.press, scholar.google.co.uk, yann.lecun.com, gatsby.ucl.ac.uk, scholar.google.ca, cs.mcgill.ca, birmingham.ac.uk, linclab.mila.quebec, is.mpg.de
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