Efficiently Dispatching Plans Encoded as Simple Temporal Problems

Efficiently Dispatching Plans Encoded as Simple Temporal Problems

Martha E. Pollack (University of Michigan, USA) and Ioannis Tsamardinos (Vanderbilt University, USA)
Copyright: © 2005 |Pages: 24
DOI: 10.4018/978-1-59140-450-7.ch009
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Abstract

The Simple Temporal Problem (STP) formalism was developed to encode flexible quantitative temporal constraints, and it has been adopted as a commonly used framework for temporal plans. This chapter addresses the question of how to automatically dispatch a plan encoded as an STP, that is, how to determine when to perform its constituent actions so as to ensure that all of its temporal constraints are satisfied. After reviewing the theory of STPs and their use in encoding plans, we present detailed descriptions of the algorithms that have been developed to date in the literature on STP dispatch. We distinguish between off-line and online dispatch, and present both basic algorithms for dispatch and techniques for improving their efficiency in time-critical situations.

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Table of Contents
Preface
Ioannis Vlahavas, Dimitris Vrakas
Acknowledgments
Chapter 1
Thomas Eiter, Wolfgang Faber, Gerald Pfeifer, Axel Polleres
This chapter introduces planning and knowledge representation in the declarative action language K. Rooted in the area of Knowledge Representation &... Sample PDF
Declarative Planning and Knowledge Representation in an Action Language
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Chapter 2
Max Garagnani
This chapter describes a model and an underlying theoretical framework for hybrid planning. Modern planning domain description languages are based... Sample PDF
A Framework for Hybrid and Analogical Planning
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Chapter 3
Dimitris Vrakas, Grigorios Tsoumakas, Nick Bassiliakes, Ioannis Vlahavas
This chapter is concerned with the enhancement of planning systems using techniques from Machine Learning in order to automatically configure their... Sample PDF
Machine Learning for Adaptive Planning
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Chapter 4
José Luis Ambite, Craig A. Knoblock, Steven Minton
Planning by Rewriting (PbR) is a paradigm for efficient high-quality planning that exploits declarative plan rewriting rules and efficient local... Sample PDF
Plan Optimization by Plan Rewriting
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Chapter 5
Nikos Avradinis, Themis Panayiotopoulos
This chapter discusses the application of intelligent planning techniques to virtual agent environments as a mechanism to control and generate... Sample PDF
Continuous Planning for Virtual Environments
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Chapter 6
Jeroen Valk, Mathijs de Weerdt, Cees Witteveen
Multi-agent planning comprises planning in an environment with multiple autonomous actors. Techniques for multi-agent planning differ from... Sample PDF
Coordination in Multi-Agent Planning with an Application in Logistics
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Chapter 7
Catherine C. Marinagi, Themis Panayiotopoulos, Constantine D. Spyropoulos
This chapter provides an overview of complementary research in the active research areas: AI planning technology and intelligent agents technology.... Sample PDF
AI Planning and Intelligent Agents
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Chapter 8
Amedeo Cesta, Simone Fratini, Angelo Oddi
This chapter proposes to model a planning problem (e.g., the control of a satellite system) by identifying a set of relevant components in the... Sample PDF
Planning with Concurrency, Time and Resources: A CSP-Based Approach
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Chapter 9
Martha E. Pollack, Ioannis Tsamardinos
The Simple Temporal Problem (STP) formalism was developed to encode flexible quantitative temporal constraints, and it has been adopted as a... Sample PDF
Efficiently Dispatching Plans Encoded as Simple Temporal Problems
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Chapter 10
Roman Bartak
As the current planning and scheduling technologies are coming together by assuming time and resource constraints in planning or by allowing... Sample PDF
Constraint Satisfaction for Planning and Scheduling
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About the Authors