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Preview of Residual Algorithms
🔗 Source: leemon.com
📊 Size: 249 KB
📄 Pages: 9 pages
⬇️ Downloads: 145

Summary

Reinforcement learning algorithms guaranteed to converge with lookup tables can become unstable with function-approximation systems. Residual gradient algorithms converge but may learn slowly. Residual algorithms combine the advantages of direct and residual gradient algorithms, guaranteeing convergence and fast learning speed. They can be applied to value iteration, Q-learning, and advantage learning, and their properties are explained through theoretical analysis and simulation results.

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Description

Reinforcement learning algorithms guaranteed to converge with lookup tables can become unstable with function-approximation systems.

Technical Information

  • File Format: PDF
  • File Size: 249 KB
  • Pages: 9
  • Language: EN
  • Total Downloads: 145
  • Last Updated: 2 weeks ago

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