Focused Dynamic Programming: Extensive Comparative Results

Abstract

We present a heuristic-based propagation algorithm for solving restricted Markov decision processes (MDPs). Our approach, which combines ideas from deterministic search and recent dynamic programming methods, focuses computation towards promising areas of the state space. It is thus able to significantly reduce the amount of processing required in producing a solution. We present a number of results comparing our approach to existing algorithms on a robotic path planning domain.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2004
Accession Number
ADA528892

Entities

People

  • Anthony Stentz
  • Dave Ferguson

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Autonomy
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Computations
  • Computer Programming
  • Convergence
  • Dynamic Programming
  • Environment
  • Equations
  • Errors
  • Evolutionary Algorithms
  • Heuristic Methods
  • Iterations
  • Motion Planning
  • Probability
  • Probability Distributions
  • Robotics
  • Standards

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Mathematical Modeling and Probability Theory.
  • Software Engineering.

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms
  • Autonomy
  • Autonomy - Autonomous System Control
  • Space