OBDD-based Universal Planning for Synchronized Agents in Non-Deterministic Domains

Abstract

Recently model checking representation and search techniques were shown to be efficiently applicable to planning, in particular to non-deterministic planning. Such planning approaches use Ordered Binary Decision Diagrams (OBDDS) to encode a planning domain as a non-deterministic finite automaton and then apply fast algorithms from model checking to search for a solution. OBDDS can effectively scale and can provide universal plans for complex planning domains. We are particular interested in addressing the complexities arising in non-deterministic, multi-agent domains. In this article, we present UMOP, a new universal OBDD-based planning framework for non-deterministic, multi-agent domains. We introduce a new planning domain description language. NADL, to specify non-deterministic, multi-agent domains. The language contributes the explicit definition of controllable agents and uncontrollable environment agents. We describe the syntax and semantics of NADL and show how to build an efficient OBDD-based representation of an NADL description.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2000
Accession Number
ADA640688

Entities

People

  • Manuela M. Veloso
  • Rune M. Jensen

Organizations

  • Carnegie Institute of Technology

Tags

Communities of Interest

  • Autonomy
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Abstracts
  • Air Force
  • Air Force Research Laboratories
  • Algorithms
  • Arithmetic
  • Artificial Intelligence
  • Coding
  • Computations
  • Energy Production
  • Failed States
  • Heat Exchangers
  • Information Systems
  • Intelligence Planning
  • Language
  • Notation
  • Reinforcement Learning
  • Two Dimensional

Fields of Study

  • Computer science

Readers

  • Computational Linguistics
  • Parasitology and Pharmacology of Malaria.
  • Robotics and Automation.