The Use of Multiple Problem Decompositions in Time Constrained Planning Tasks,

Abstract

Problems requiring the synthesis of a collection of plans accomplishing distinct (but possibly related) goals has received increasing attention within artificial intelligence. Such problems are typically formulated as multi-agent planning problems, emphasizing a problem decomposition wherein individual agents assume responsibility for the generation of individual plans while taking into account the goals and beliefs of other agents in the system. One consequence of such a problem decomposition is a simplified view of resource allocations that assumes avoidance of conflicts to be the sole concern. The validity of this assumption comes into question in time constrained problem domains requiring the allocation of multiple, shared resources. In job shop scheduling for example, where sequences of manufacturing operations must be determined and scheduled for multiple orders, it is necessary to consider much more than availability to efficiently allocate resources over time. This document argues that in such domains, an ability to reason from both resource-based and agent-based perspectives is essential to appropriate consideration of all domain constraints.

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Document Details

Document Type
Technical Report
Publication Date
May 06, 1985
Accession Number
ADA158721

Entities

People

  • S. O. Peng
  • Stephen F. Smith

Organizations

  • Carnegie Institute of Technology

Tags

Communities of Interest

  • Autonomy
  • Human Systems
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Air Force
  • Artificial Intelligence
  • Availability
  • Classification
  • Decomposition
  • Demographic Cohorts
  • Intelligent Systems
  • Job Shop Scheduling
  • Manufacturing
  • Mathematics
  • Milling Machines
  • North Carolina
  • Operations Research
  • Reasoning
  • Scheduling (Production)
  • Security
  • Time Intervals

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Operations Research
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms