File:Challenges and Tricks of Deep RL.jpg
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English: This figure lists 11 popular tricks for deep reinforcement learning algorithms, as well as what kind of challenges each trick mainly addresses. These tricks include experience replay (ExR), parallel exploration (PEx), separated target network (STN), delayed policy update (DPU), constrained policy update (CPU), clipped actor criterion (CAC), double Q-functions (DQF), bounded double Q-functions (BDQ), distributional return function (DRF), entropy regularization (EnR), and soft value function (SVF). |
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| Source | Own work |
| Author | Tsesea |
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I, the copyright holder of this work, hereby publish it under the following license:
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| Date/Time | Thumbnail | Dimensions | User | Comment | |
|---|---|---|---|---|---|
| current | 00:50, 6 December 2023 | | 1,215 × 1,093 (90 KB) | Tsesea (talk | contribs) | Uploaded while editing "Deep reinforcement learning" on en.wikipedia.org |
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