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Reinforcement Learning.pdf

Kober_IJRR_2013.pdf
Preview of Reinforcement Learning
🔗 Source: ri.cmu.edu
📊 Size: 1.37 MB
📄 Pages: 73 pages
⬇️ Downloads: 134

Summary

Reinforcement learning offers a framework for designing sophisticated robot behaviors through trial-and-error interactions with the environment, using a scalar objective function to measure performance. Robots have learned various tasks, such as pushing boxes, peg-in-hole insertion, and flight control, using reinforcement learning approaches like value function-based and policy search methods. The relationship between reinforcement learning and robotics is promising, with robotics providing challenges that inspire developments in reinforcement learning, and reinforcement learning offering tools for designing complex behaviors. Key challenges in robot reinforcement learning include complexity of the domain, choice between model-based and model-free methods, and role of algorithms, representations, and prior knowledge.

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Description

Reinforcement learning offers a framework for designing sophisticated robot behaviors through trial-and-error interactions with the environment, using a scalar...

Technical Information

  • File Format: PDF
  • File Size: 1.37 MB
  • Pages: 73
  • Language: EN
  • Total Downloads: 134
  • Last Updated: 2 weeks ago

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This PDF document about Reinforcement Learning provides comprehensive information and guidance. Whether you're a beginner or advanced user, this resource offers valuable insights into Reinforcement Learning.

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