Generative Adversarial Imitation Learning presents a new general framework for directly extracting a policy from data, as if it were obtained by reinforcement learning following inverse reinforcement learning.
Source: Generative Adversarial Imitation LearningPaper | Code | Results | Date | Stars |
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Task | Papers | Share |
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Imitation Learning | 31 | 48.44% |
Reinforcement Learning (RL) | 12 | 18.75% |
Continuous Control | 4 | 6.25% |
Autonomous Driving | 2 | 3.13% |
Autonomous Navigation | 2 | 3.13% |
Navigate | 1 | 1.56% |
Decoder | 1 | 1.56% |
Quantization | 1 | 1.56% |
Denoising | 1 | 1.56% |
Component | Type |
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🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |