Explainable and Interpretable Reinforcement Learning for Robotics - Dinesh Manocha,Elham Tabassi,Aaron M. Roth,Ram D. Sriram
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This book surveys the state of the art in explainable and interpretable reinforcement learning (RL) as relevant for robotics. While RL in general has grown in popularity and been applied to increasingly complex problems, several challenges have impeded the real-world adoption of RL algorithms for robotics and related areas. These include difficulties in preventing safety constraints from being violated and ... Full description
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Description
More Information
| Author | Dinesh Manocha, Elham Tabassi, Aaron M. Roth, Ram D. Sriram |
|---|---|
| Publisher | Springer Nature Switzerland |
| Series | Synthesis Lectures on Artificial Intelligence and Machine Learning |
| Release year | 2024 |
| Cover type | Hardcover |
| EAN | 9783031475177 |