Institute of Information Theory and Automation

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AS Seminar: Transfer learning in Reinforcement learning tasks

2022-04-04 10:30

Deep reinforcement learning has shown an ability to achieve super-human performance in solving complex reinforcement learning tasks only from raw-pixels. However, it fails to reuse knowledge from previously learnt tasks to solve new, unseen ones. To generalize and reuse knowledge is one of the fundamental requirements for creating a truly intelligent agent. The work summarizes the problem of transfer learning in reinforcement learning tasks and offers a method for one-to-one task transfer learning.

2022-06-29 12:15