article

Integer optimization models of AI planning problems

Authors:

Henry Kautz and

Joachim P. WalserAuthors Info & Claims

The Knowledge Engineering Review, Volume 15, Issue 1

Pages 101 - 117

https://doi.org/10.1017/S0269888900001053

Published: 01 March 2000 Publication History

Abstract

This paper describes ILP-PLAN, a framework for solving AI planning problems represented as integer linear programs. ILP-PLAN extends the planning as satisfiability framework to handle plans with resources, action costs, and complex objective functions. We show that challenging planning problems can be effectively solved using both traditional branch-and-bound integer programming solvers and efficient new integer local search algorithms. ILP-PLAN can find better quality solutions for a set of hard benchmark logistics planning problems than had been found by any earlier system.

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Cited By

Coles AColes AFox MLong D(2013)A hybrid LP-RPG heuristic for modelling numeric resource flows in planningJournal of Artificial Intelligence Research10.5555/2512538.251254846:1(343-412)Online publication date: 1-Jan-2013
https://dl.acm.org/doi/10.5555/2512538.2512548
Pralet CVerfaillie G(2012)Combining static and dynamic models for boosting forward planningProceedings of the 9th international conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems10.1007/978-3-642-29828-8_21(322-338)Online publication date: 28-May-2012
https://dl.acm.org/doi/10.1007/978-3-642-29828-8_21
Wu JDurfee E(2010)Resource-driven mission-phasing techniques for constrained agents in stochastic environmentsJournal of Artificial Intelligence Research10.5555/1892211.189222238:1(415-473)Online publication date: 1-May-2010
https://dl.acm.org/doi/10.5555/1892211.1892222
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Index Terms

Integer optimization models of AI planning problems
1. Mathematics of computing
  1. Mathematical analysis
    1. Mathematical optimization
      1. Mixed discrete-continuous optimization
        Integer programming
2. Theory of computation
  1. Design and analysis of algorithms
    1. Mathematical optimization
      1. Mixed discrete-continuous optimization
        Integer programming

Index terms have been assigned to the content through auto-classification.

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cover image The Knowledge Engineering Review

The Knowledge Engineering Review Volume 15, Issue 1

March 2000

115 pages

ISSN:0269-8889

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Cambridge University Press

United States

Publication History

Published: 01 March 2000

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Cited By

Coles AColes AFox MLong D(2013)A hybrid LP-RPG heuristic for modelling numeric resource flows in planningJournal of Artificial Intelligence Research10.5555/2512538.251254846:1(343-412)Online publication date: 1-Jan-2013
https://dl.acm.org/doi/10.5555/2512538.2512548
Pralet CVerfaillie G(2012)Combining static and dynamic models for boosting forward planningProceedings of the 9th international conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems10.1007/978-3-642-29828-8_21(322-338)Online publication date: 28-May-2012
https://dl.acm.org/doi/10.1007/978-3-642-29828-8_21
Wu JDurfee E(2010)Resource-driven mission-phasing techniques for constrained agents in stochastic environmentsJournal of Artificial Intelligence Research10.5555/1892211.189222238:1(415-473)Online publication date: 1-May-2010
https://dl.acm.org/doi/10.5555/1892211.1892222
Coles AFox MLong DSmith A(2008)A hybrid relaxed planning graph-LP heuristic for numeric planning domainsProceedings of the Eighteenth International Conference on International Conference on Automated Planning and Scheduling10.5555/3037281.3037289(52-59)Online publication date: 14-Sep-2008
https://dl.acm.org/doi/10.5555/3037281.3037289
Crawford J(2008)Lessons Learned Delivering Optimized Supply‐Chain Planning to the Business WorldAI Magazine10.1609/aimag.v29i2.210729:2(51-56)Online publication date: 1-Jun-2008
https://dl.acm.org/doi/10.1609/aimag.v29i2.2107
Chen YXing ZZhang W(2007)Long-distance mutual exclusion for propositional planningProceedings of the 20th international joint conference on Artifical intelligence10.5555/1625275.1625573(1840-1845)Online publication date: 6-Jan-2007
https://dl.acm.org/doi/10.5555/1625275.1625573
Wu JDurfee EDurfee EYokoo MHuhns MShehory O(2007)Sequential resource allocation in multiagent systems with uncertaintiesProceedings of the 6th international joint conference on Autonomous agents and multiagent systems10.1145/1329125.1329265(1-8)Online publication date: 14-May-2007
https://dl.acm.org/doi/10.1145/1329125.1329265
Chen YWah BHsu C(2006)Temporal planning using subgoal partitioning and resolution in SGPlanJournal of Artificial Intelligence Research10.5555/1622559.162256826:1(323-369)Online publication date: 1-Aug-2006
https://dl.acm.org/doi/10.5555/1622559.1622568
Wah BChen Y(2006)Constraint partitioning in penalty formulations for solving temporal planning problemsArtificial Intelligence10.5555/1141151.1644640170:3(187-231)Online publication date: 1-Mar-2006
https://dl.acm.org/doi/10.5555/1141151.1644640
Wu JDurfee EPechoucek MSteiner DThompson S(2005)Automated resource-driven mission phasing techniques for constrained agentsProceedings of the fourth international joint conference on Autonomous agents and multiagent systems10.1145/1082473.1082524(331-338)Online publication date: 25-Jul-2005
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