Symbolic Dynamic Programming for Discrete and Continuous State MDPs

  title={Symbolic Dynamic Programming for Discrete and Continuous State MDPs},
  author={Scott Sanner and Karina Valdivia Delgado and Leliane Nunes de Barros},
Many real-world decision-theoretic planning problems can be naturally modeled with discrete and continuous state Markov decision processes (DC-MDPs). While previous work has addressed automated decision-theoretic planning for DCMDPs, optimal solutions have only been defined so far for limited settings, e.g., DC-MDPs having hyper-rectangular piecewise linear value functions. In this work, we extend symbolic dynamic programming (SDP) techniques to provide optimal solutions for a vastly expanded… CONTINUE READING


Publications referenced by this paper.
Showing 1-10 of 19 references

A model for reasoning about persistence and causation

  • Thomas Dean, Keiji Kanazawa
  • Computational Intelligence,
  • 1989
Highly Influential
5 Excerpts

Littman . Lazy approximation for solving continuous finitehorizon mdps

  • Lihong Li, L. Michael
  • 2005

Similar Papers

Loading similar papers…