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Ensuring the Satisfaction of Structural Constraints

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Constraint-Based Agents

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2062))

Abstract

For smaller applications, it is not necessary to implement a system that supports full structural satisfaction, and — as described in Chap. 5 — this has not been implemented for the test runs described in this book. However, in such cases, it must be proved that the system cannot reach a structurally inconsistent state. This has the drawback that the system is highly inflexible because these proofs have to be redone/rechecked each time the problem specification or the solving mechanisms are changed. Thus, from a software engineering point of view, the better choice is a full implementation of the structural satisfaction (see Sect. 3.7).

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References

  1. Aarts, E. H. L., and Lenstra, J. K. eds. 1997. Local search in Combinatorial Optimization. Reading, Wiley-Interscience.

    Google Scholar 

  2. Agre, P., and Chapman, D. 1987. PENGI: An Implementation of a Theory of Activity. In Proceedings of the Sixth National Conference on Artificial Intelligence (AAAI-87), 268–272.

    Google Scholar 

  3. Allen, J. F. 1983. Maintaining Knowledge about Temporal Intervals. Communications of the ACM 26(11): 832–843.

    Article  MATH  Google Scholar 

  4. Allen, J. F. 1984. Towards a General Theory of Action and Time. Artificial Intelligence 23: 123–154.

    Article  MATH  Google Scholar 

  5. Allen, J. F., and Ferguson, G. 1994. Actions and Events in Interval Temporal Logic. Journal of Logic and Computation 4(5): 531–579.

    Article  MATH  MathSciNet  Google Scholar 

  6. Allis, L. V.; Van den Herik, H. J.; and Huntjens, M. P. H. 1993. Go-Moku Solved by New Search Techniques. In Proceedings of the 1993 AAAI Fall Symposium on Games: Planning and Learning.

    Google Scholar 

  7. Ambite, J. L., and Knoblock, C. A. 1997. Planning by Rewriting: Efficiently Generating High-Quality Plans. In Proceedings of the Fourteenth National Conference on Artificial Intelligence (AAAI-97), 706–713.

    Google Scholar 

  8. Ambite, J. L.; Knoblock, C. A.; and Minton, S. 2000. Learning Plan Rewriting Rules. In Proceedings of the Fifth International Conference on Artificial Intelligence Planning and Scheduling (AIPS-2000).

    Google Scholar 

  9. Ambros-Ingerson, J. A., and Steel, S. 1988. Integrating Planning, Execution and Monitoring. In Proceedings of the Seventh National Conference on Artificial Intelligence (AAAI-88), 83–88.

    Google Scholar 

  10. Babaian, T., and Schmolze, J. G. 1999. PSIPLAN: Planning with-forms over Partially Closed Worlds. In Proceedings of the Fifth European Conference on Planning (ECP’99).

    Google Scholar 

  11. Bacchus, F., and Kabanza, F. 2000. Using Temporal Logics to Express Search Control Knowledge for Planning. Artificial Intelligence 116: 123–191.

    Article  MATH  MathSciNet  Google Scholar 

  12. Baptiste, P., and Le Pape, C. 1995. A Theoretical and Experimental Comparison of Constraint Propagation Techniques for Disjunctive Scheduling. In Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence (IJCAI-95), 600–606.

    Google Scholar 

  13. Barbulescu, L.; Watson, J.-P.; and Whitley, L. D. 2000. In Proceedings of the Seventeenth National Conference on Artificial Intelligence (AAAI-2000), 879–884.

    Google Scholar 

  14. Barto, A. G.; Bradtke, S. J.; and Singh, S. P. 1995. Learning to Act using Real-Time Dynamic Programming. Artificial Intelligence 72(1): 81–138.

    Article  Google Scholar 

  15. Bessière, C.; Freuder, E. C.; and Règin, J.-Ch. 1995. Using Inference to Reduce Arc Consistency Computation. In Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence (IJCAI-95), 592–598.

    Google Scholar 

  16. Blum, A. L., and Furst, M. L. 1997. Fast Planning Through Planning Graph Analysis. Artificial Intelligence 90: 281–300.

    Article  MATH  Google Scholar 

  17. Bockmayr, A., and Kasper, T. 1998. Branch-and-Infer: A Unifying Framework for Integer and Finite Domain Constraint Programming. INFORMS Journal on Computing 10(3): 287–300.

    Article  MATH  MathSciNet  Google Scholar 

  18. Bockmayr, A., and Dimopoulos, Y. 1998. Mixed Integer Programming Models for Planning Problems. In Working Notes of the CP98Workshop on Constraint Problem Reformulation.

    Google Scholar 

  19. Bonasso, R. P.; Firby, R. J.; Gat, E.; Kortenkamp, D.; Miller, D. P.; and Slack, M. G. 1997. Experiences with an Architecture for Intelligent, Reactive Agents. Journal of Experimental and Theoretical Artificial Intelligence 9(1).

    Google Scholar 

  20. Bonet, B.; Loerincs, G.; and Géner, H. 1997. A Robust and Fast Action Selection Mechanism for Planning. In Proceedings of the Fourteenth National Conference on Artificial Intelligence (AAAI-97), 714–719.

    Google Scholar 

  21. Boutilier, C., and Brafman, R. I. 1997. Planning with Concurrent Interacting Actions. In Proceedings of the Fourteenth National Conference on Artificial Intelligence (AAAI-97), 720–726.

    Google Scholar 

  22. Boutilier, C.; Dean, T.; and Hanks, S. 1999. Decision-Theoretic Planning: Structural Assumptions and Computational Leverage. Journal of Artificial Intelligence Research 11: 1–94.

    MATH  MathSciNet  Google Scholar 

  23. Brafman, R. I., and Hoos, H. H. 1999. To Encode or not to Encode-I: Linear Planning. In Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence (IJCAI-99), 988–993.

    Google Scholar 

  24. Bresina, J. L. 1996. Heuristic-Biased Stochastic Sampling. In Proceedings of the Thirteenth National Conference on Artificial Intelligence (AAAI-96), 271–278.

    Google Scholar 

  25. Brooks, R. A. 1986. A Robust Layered Control System for a Mobile Robot. IEEE Journal of Robotics and Automation RA-2 (1): 14–23.

    Google Scholar 

  26. Carlier, J., and Pinson, E. 1990. A Practical Use of Jackson’s Preemptive Schedule for Solving the Job-Shop Problem. Annals of Operations Research 26: 269–287.

    MATH  MathSciNet  Google Scholar 

  27. Caseau, Y., and Laburthe, F. 1994. Improved CLP Scheduling with Task Intervals. In Proceedings of the Eleventh International Conference on Logic Programming (ICLP’94), 369–383.

    Google Scholar 

  28. Chapman, D. 1987. Planning for Conjunctive Goals. Artificial Intelligence 32(3): 333–377.

    Article  MATH  MathSciNet  Google Scholar 

  29. Charla, C. 1995. Mind Games: the Rise and Rise of Artificial Intelligence. Next Generation 11/95.

    Google Scholar 

  30. Chien, S.; Knight, R.; Stechert, A.; Sherwood, R.; and Rabideau, G. 2000. Using Iterative Repair to Improve the Responsiveness of Planning and Scheduling. In Proceedings of the Fifth International Conference on Artificial Intelligence Planning and Scheduling (AIPS-2000).

    Google Scholar 

  31. Chien, S.; Rabideau, G.; Knight, R.; Sherwood, R.; Engelhardt, B.; Mutz, D.; Estlin, T.; Smith, B.; Fisher, F.; Barrett, T.; Stebbins, G.; and Tran, D. 2000. ASPEN-Automating Space Mission Operations using Automated Planning and Scheduling. In Proceedings of the Sixth International Symposium on Technical Interchange for Space Mission Operations and Ground Data Systems (SpaceOps 2000).

    Google Scholar 

  32. Coco, D. 1997. Creating Intelligent Creatures. Computer Graphics World, July 1997.

    Google Scholar 

  33. Coradeschi, S., and Saffiotti, A. 2000. Anchoring Symbols to Sensor Data: preliminary report. In Proceedings of the Seventeenth National Conference on Artificial Intelligence (AAAI-2000), 129–135.

    Google Scholar 

  34. Danzig, G. B. 1963. Linear Programming and Extensions. Princeton University Press.

    Google Scholar 

  35. Davenport, A.; Tsang, E.; Wang, C. W.; and Zhu, K. 1994. GENET: A Connectionist Architecture for Solving Constraint Satisfaction Problems by Iterative Improvement. In Proceedings of the Twelfth National Conference on Artificial Intelligence (AAAI-94), 325–330.

    Google Scholar 

  36. Davis, M., and Putnam, H. 1960. A Computation Procedure for Quantification Theory. Journal of the ACM 7(3): 201–215.

    Article  MATH  MathSciNet  Google Scholar 

  37. Dean, T.; Kaelbling, L. P.; Kirman, J.; and Nicholson, A. 1995. Planning under Time Constraints in Stochastic Domains. Artificial Intelligence 76: 35–74.

    Article  Google Scholar 

  38. Dechter, R. 1990. Enhancement Schemes for Constraint Processing: Backjumping, Learning, and Cutset Decomposition. Artificial Intelligence 41: 273–312.

    Article  MathSciNet  Google Scholar 

  39. Dechter, R.; Meiri, I.; and Pearl, J. 1991. Temporal Constraint Networks. Artificial Intelligence 49: 61–95.

    Article  MATH  MathSciNet  Google Scholar 

  40. Dijkstra, E. W. 1959. A note on two problems in connexion with graphs. Numerische Mathematik, 1: 269–271.

    Article  MATH  MathSciNet  Google Scholar 

  41. Do, B., and Kambhampati, S. 2000. Solving Planning Graph by Compiling it into a CSP. In Proceedings of the Fifth International Conference on Artificial Intelligence Planning and Scheduling (AIPS-2000).

    Google Scholar 

  42. Dorigo, M.; Di Caro, G.; and Gambardella, L. M. 1999. Ant Algorithms for Discrete Optimization. Artificial Life 5(3), 137–172.

    Article  Google Scholar 

  43. Drabble, B. 1993. Excalibur: A Program for Planning and Reasoning with Processes. Artificial Intelligence 62(1): 1–40.

    Article  Google Scholar 

  44. Drabble, B. and Tate, A. 1994. The Use of Optimistic and Pessimistic Resource Profiles to Inform Search in an Activity Based Planner. In Proceedings of the Second International Conference on AI Planning Systems (AIPS-94), 243–248.

    Google Scholar 

  45. Drabble, B.; Dalton, J.; and Tate, A. 1997. Repairing Plans on the Fly. In Proceedings of the 1997 NASA Workshop on Planning and Scheduling for Space.

    Google Scholar 

  46. d’Inverno, M.; Kinny, D.; Luck, M.; and Wooldridge, M. 1997. A formal specification of dMARS. Technical Report 72, Australian Artificial Intelligence Institute, Melbourne, Australia.

    Google Scholar 

  47. Draper, D.; Hanks, S.; and Weld, D. 1994. Probabilistic Planning with Information Gathering and Contingent Execution. In Proceedings of the Second International Conference on AI Planning Systems (AIPS-94), 31–36.

    Google Scholar 

  48. Drummond, M. E., and Bresina, J. L. 1990. Anytime Synthetic Projection: Maximizing the Probability of Goal Satisfaction. In Proceedings of the Eighth National Conference on Artificial Intelligence (AAAI-90), 138–144.

    Google Scholar 

  49. Ehrig, H.; Pfender, M.; and Schneider, H. J. 1973. Graph Grammars: An Algebraic Approach. In Proceedings of the Fourteenth Annual Symposium on Switching and Automata Theory (SWAT), 167–180.

    Google Scholar 

  50. El-Kholy, A., and Richards, B. 1996. Temporal and Resource Reasoning in Planning: the parcPLAN approach. In Proceedings of the Twelfth European Conference on Artificial Intelligence (ECAI-96), 614–618.

    Google Scholar 

  51. Engelhardt, B., and Chien, S. 2000. An Empirical Analysis of Local Search in Stochastic Optimization for Planner Strategy Selection. In Workshop Notes of the ECAI-2000 Workshop on Local Search for Planning & Scheduling, 10–16.

    Google Scholar 

  52. Ephrati, E.; Pollack, M. E.; and Milshtein, M. 1996. A Cost-Directed Planner: Preliminary Report. In Proceedings of the Thirteenth National Conference on Artificial Intelligence (AAAI-96), 1223–1228.

    Google Scholar 

  53. Erol, K.; Nau, D. S.; and Subrahmanian, V. S. 1991. Complexity, Decidability and Undecidability Results for Domain-Independent Planning. Technical Report CS-TR-2797, University of Maryland, Institute for Advanced Computer Studies, Maryland, USA.

    Google Scholar 

  54. Etzioni, O.; Hanks, S.; Weld, D.; Draper, D.; Lesh, N.; and Williamson, M. 1992. An Approach to Planning with Incomplete Information. In Proceedings of the Third International Conference on Principles of Knowledge Representation and Reasoning (KR’92).

    Google Scholar 

  55. Fikes, R. E., and Nilsson, N. 1971. STRIPS: A New Approach to the Application of Theorem Proving to Problem Solving. Artificial Intelligence 5(2): 189–208.

    Article  Google Scholar 

  56. Frank, J. 1997. Learning Short-Term Weights for GSAT. In Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence (IJCAI-97), 384–391.

    Google Scholar 

  57. Freksa, C. 1992. Temporal Reasoning Based on Semi-Intervals. Artificial Intelligence 54: 199–227.

    Article  MathSciNet  Google Scholar 

  58. Freuder, E. C., and Wallace, R. J. 1992. Partial Constraint Satisfaction. Artificial Intelligence 58: 21–70.

    Article  MathSciNet  Google Scholar 

  59. Funge, J.; Tu, X; and Terzopoulos, D. 1999. Cognitive Modeling: Knowledge, Reasoning and Planning for Intelligent Characters. In Proceedings of the International Conference on Computer Graphics and Interactive Techniques (SIGGRAPH’99), 29–38.

    Google Scholar 

  60. Gamma, E.; Helm, R.; Johnson, R.; and Vlissides, J. 1995. Design Patterns: Elements of Reusable Object-Oriented Software. Reading, Addison-Wesley Professional Computing Series.

    Google Scholar 

  61. Gard, T. 2000. Building Character. Gamasutra, June 2000. http://www.gamasutra.com/features/20000720/gard_01.htm

  62. Gasser, R. 1996. Solving Nine Men’s Morris. Computational Intelligence 12(1): 24–41.

    Article  Google Scholar 

  63. Gelfond, M., and Lifschitz, V. 1992. Representing Actions in Extended Logic Programming. In Proceedings of the Joint International Conference and Symposium on Logic Programming (JICSLP’92), 559–573.

    Google Scholar 

  64. Gent, I. P.; MacIntyre, E.; Prosser, P.; and Walsh, T. 1997. The Scaling of Search Cost. In Proceedings of the Fourteenth National Conference on Artificial Intelligence (AAAI-97), 315–320.

    Google Scholar 

  65. Gent, I. P., and Walsh, T. 1993. Towards an Understanding of Hill-climbing Procedures for SAT. In Proceedings of Eleventh National Conference on Artificial Intelligence (AAAI-93), 28–33.

    Google Scholar 

  66. Georgé, M. P., and Lansky, A. L. 1987. Reactive Reasoning and Planning. In Proceedings of the Sixth National Conference on Artificial Intelligence (AAAI87), 677–682.

    Google Scholar 

  67. Gerevini, A., and Serina, I. 1999. Fast Planning through Greedy Action Graphs. In Proceedings of the Sixteenth National Conference on Artificial Intelligence (AAAI-99), 503–510.

    Google Scholar 

  68. Glover, F. 1989. Tabu Search-Part I. ORSA Journal on Computing 1(3): 190–206.

    MATH  Google Scholar 

  69. Goldberg, D. E. 1989. Genetic Algorithms in Search, Optimization, and Machine Learning. Addison-Wesley.

    Google Scholar 

  70. Golden, K., Etzioni, O., and Weld, D. 1994. Omnipotence Without Omniscience: Efficient Sensor Management for Planning. In Proceedings of the Twelfth National Conference on Artificial Intelligence (AAAI-94), 1048–1054.

    Google Scholar 

  71. Goldman, R. P., and Boddy, M. S. 1994. Conditional Linear Planning. In Proceedings of the Second International Conference on AI Planning Systems (AIPS-94), 80–85.

    Google Scholar 

  72. Goldman, R. P., Haigh, K. Z.; Musliner, D. J.; and Pelican, M. 2000. MACBeth: A Multi-Agent Constraint-Based Planner. In Papers from the AAAI2000 Workshop on Constraints and AI Planning, Technical Report, WS-00-02, 11–17. AAAI Press, Menlo Park, California.

    Google Scholar 

  73. Goltz, H.-J. 1995. Reducing Domains for Search in CLP(FD) and Its Application to Job-Shop Scheduling. In Proceedings of the First International Conference on Principles and Practice of Constraint Programming (CP95), 549–562.

    Google Scholar 

  74. Goltz, H.-J. 1997. Redundante Constraints und Heuristiken zum effizienten Lösen von Problemen der Ablaufplanung mit CHIP. In Proceedings of the 12. Workshop on Logic Programming (WLP’97), Forschungsbericht PMS-FB1997-10, LMU München, Germany.

    Google Scholar 

  75. Gomes, C.; Selman, B.; and Kautz, H. 1998. Boosting Combinatorial Search Through Randomization. In Proceedings of the Fifteenth National Conference on Artificial Intelligence (AAAI-98), 431–437.

    Google Scholar 

  76. Gomes, C. P.; Selman, B.; Crato, N.; Kautz, H. A. 2000. Heavy-Tailed Phenomena in Satisfiability and Constraint Satisfaction Problems. Journal of Automated Reasoning 24(1/2): 67–100.

    Article  MATH  MathSciNet  Google Scholar 

  77. Grand, S.; Cliff, D.; and Malhotra, A. 1997. Creatures: Artificial Life Autonomous Software Agents for Home Entertainment. In Proceedings of the First International Conference on Autonomous Agents (Agents’97), 22–29.

    Google Scholar 

  78. Gu, J. 1992. Efficient Local Search for Very Large-Scale Satisfiability Problems. SIGART Bulletin 3(1): 8–12.

    Article  Google Scholar 

  79. Habel, A.; Heckel, R.; and Taentzer, G. 1996. Graph Grammars with Negative Application Conditions. Fundamenta Informaticae, Vol. 26, No. 3 & 4.

    Google Scholar 

  80. Hammond, K. J. 1990. Case-Based Planning: A Framework for Planning from Experience. The Journal of Cognitive Science, 14(3): 385–443.

    Article  Google Scholar 

  81. Han, C., and Lee, C. 1988. Comments on Mohr and Henderson’s Path Consistency Algorithm. Artificial Intelligence 36, 125–130.

    Article  MATH  Google Scholar 

  82. Hart, P. E.; Nilsson, N. J.; and Raphael, B. 1968. A formal basis for the heuristic determination of minimum cost paths. IEEE Transactions on Systems Science and Cybernetics 4(2): 100–107.

    Article  Google Scholar 

  83. Harvey, W. D., and Ginsberg, M. L. 1995. Limited Discrepancy Search. In Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence (IJCAI-95), 607–615.

    Google Scholar 

  84. Hause, K. 1999. What to Play Next: Gaming Forecast, 1999-2003. Report #W21056, International Data Corporation, Framingham, Massachusetts.

    Google Scholar 

  85. Heckel, R., and Wagner, A. 1995. Ensuring Consistency of Conditional Graph Rewriting-a Constructive Approach. In Proceedings of the Joint COMPUGRAPH/SEMAGRAPH Workshop on Graph Rewriting and Computation (SEGRAGRA’95).

    Google Scholar 

  86. Hirayama, K., and Toyoda, J. 1995. Forming Coalitions for Breaking Deadlocks. In Proceedings of the First International Conference on Multi-Agent Systems (ICMAS-95), 155–162.

    Google Scholar 

  87. Hoffmann, J. 2000. A Heuristic for Domain Independent Planning and its Use in an Enforced Hill-climbing Algorithm. In Proceedings of the Twelfth International Symposium on Methodologies for Intelligent Systems.

    Google Scholar 

  88. Hooker, J.; Ottosson, G.; Thorsteinsson, E. S.; and Kim, H.-J. 1999. A Scheme for Unifying Optimization and Constraint Satisfaction Methods. Knowledge Engineering Review, to appear.

    Google Scholar 

  89. ILOG, Inc. 2000. Optimization Technology White Paper-A comparative study of optimization technologies. White Paper, ILOG, Inc., Mountain View, CA.

    Google Scholar 

  90. Isbister, K. 1995. Perceived Intelligence and the Design of Computer Characters. Lifelike Computer Characters (LCC’95), Snowbird, Utah.

    Google Scholar 

  91. Jacopin, È., and Penon, J. 2000. On the Path from Classical Planning to Arithmetic Constraint Satisfaction. In Papers from the AAAI-2000 Workshop on Constraints and AI Planning, Technical Report, WS-00-02, 18–24. AAAI Press, Menlo Park, California.

    Google Scholar 

  92. Joslin, D. 1996. Passive and Active Decision Postponement in Plan Generation. PhD thesis, University of Pittsburgh, Pittsburgh, PA.

    Google Scholar 

  93. Joslin, D. E., and Clements, D. P. 1999. Squeaky Wheel Optimization. Journal of Artificial Intelligence Research 10, 353–373.

    MATH  MathSciNet  Google Scholar 

  94. Junker, U. 2000. Preference-based Search for Scheduling. In Proceedings of the Seventeenth National Conference on Artificial Intelligence (AAAI-2000), 904–909.

    Google Scholar 

  95. Jussien, N., and Lhomme, O. 2000. Local search with constraint propagation and conflict-based heuristics. In Proceedings of the Seventeenth National Conference on Artificial Intelligence (AAAI-2000), 169–174.

    Google Scholar 

  96. Kakas, A., and Miller, R. 1997. A Simple Declarative Language for Describing Narratives with Actions. The Journal of Logic Programming 31: 157–200.

    Article  MATH  MathSciNet  Google Scholar 

  97. Karmarkar, N. 1984. A New Polynomial-Time Algorithm for Linear Programming. Combinatorica 4: 373–395.

    Article  MATH  MathSciNet  Google Scholar 

  98. Kautz, H., and Selman, B. 1992. Planning as Satisfiability. In Proceedings of the Tenth European Conference on Artificial Intelligence (ECAI-92), 359–363.

    Google Scholar 

  99. Kautz, H., and Selman, B. 1996. Pushing the Envelope: Planning, Propositional Logic, and Stochastic Search. In Proceedings of the Thirteenth National Conference on Artificial Intelligence (AAAI-96), 1194–1201.

    Google Scholar 

  100. Kautz, H., and Selman, B. 1998. BLACKBOX: A New Approach to the Application of Theorem Proving to Problem Solving. In Working Notes of the AIPS-98 Workshop on Planning as Combinatorial Search, 58–60.

    Google Scholar 

  101. Kautz, H., and Walser, J. P. 1999. State-space Planning by Integer Optimization. In Proceedings of the Sixteenth National Conference on Artificial Intelligence (AAAI-99), 526–533.

    Google Scholar 

  102. Kirkpatrick, S.; Gelatt, C. D.; and Vecchi, M. P. 1983. Optimization by Simulated Annealing. Science 220(4598): 671–680.

    Article  MathSciNet  Google Scholar 

  103. Koehler, J. 1998. Planning under Resource Constraints. In Proceedings of the Thirteenth European Conference on Artificial Intelligence (ECAI-98), 489493.

    Google Scholar 

  104. Koenig, S., and Liu, Y. 2000. Representations of Decision-Theoretic Planning Tasks. In Proceedings of the Fifth International Conference on Artificial Intelligence Planning and Scheduling (AIPS-2000), 187–195.

    Google Scholar 

  105. Kondrak, G., and van Beek, P. 1997. A Theoretical Evaluation of Selected Backtracking Algorithms. Artificial Intelligence 89: 365–387.

    Article  MATH  MathSciNet  Google Scholar 

  106. Korf, R. E. 2000. Recent Progress in the Design and Analysis of Admissible Heuristic Functions. In Proceedings of the Seventeenth National Conference on Artificial Intelligence (AAAI-2000), 1165–1170.

    Google Scholar 

  107. Knoblock, C. A. 1995. Planning, Executing, Sensing, and Replanning for Information Gathering. In Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence (IJCAI-95), 1686–1693.

    Google Scholar 

  108. Kushmerick, N.; Hanks, S.; and Weld, D. 1995. An Algorithm for Probabilistic Planning. Artificial Intelligence 76: 239–286.

    Article  Google Scholar 

  109. Kwok, C. T., and Weld, D. S. 1996. Planning to Gather Information. In Proceedings of the Thirteenth National Conference on Artificial Intelligence (AAAI-96), 32–39.

    Google Scholar 

  110. Laborie, P., and Ghallab, M. 1995. Planning with Sharable Resource Constraints. In Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence (IJCAI-95), 1643–1649.

    Google Scholar 

  111. Le Pape, C. 1994. Implementation of Resource Constraints in ILOG Schedule: A Library for the Development of Constraint-Based Scheduling Systems. Intelligent Systems Engineering 3(2): 55–66.

    Article  Google Scholar 

  112. Lieber, J., and Napoli, A. 1996. Using Classification in Case-Based Planning. In Proceedings of the Twelfth European Conference on Artificial Intelligence (ECAI-96), 132–137.

    Google Scholar 

  113. Malik, J., and Binford, T. O. 1983. Reasoning in Time and Space. In Proceedings of the Eighth International Joint Conference on Artificial Intelligence (IJCAI-83), 343–345.

    Google Scholar 

  114. Martin, D. L.; Cheyer, A. J.; and Moran, D. B. 1999. The open agent architecture: A framework for building distributed software systems. Applied Artificial Intelligence 13: 91–128.

    Article  Google Scholar 

  115. Mattsson, C. 2000. The Tolkien Monster Encyclopedia. http://home7.swipnet.se/~w-70531/Tolkien/

  116. McAllester, D; Selman, B.; and Kautz, H. 1997. Evidence for Invariants in Local Search. In Proceedings of the Fourteenth National Conference on Artificial Intelligence (AAAI-97), 321–326.

    Google Scholar 

  117. Meyer auf’m Hofe, H. 1998. Finding Regions for Local Repair in Partial Constraint Satisfaction. In Proceedings of the Twentysecond Annual German Conference on Artificial Intelligence (KI-98).

    Google Scholar 

  118. McCarthy, J., and Hayes, P. J. 1969. Some Philosophical Problems from the Standpoint of Artificial Intelligence. In Meltzer, B., and Mitchie, D. (eds.), Machine Intelligence 4, Edinburgh University Press.

    Google Scholar 

  119. Milano, M.; Ottosson, G.; Refalo, P.; and Thorsteinsson, E. S. 2000. The Benfits of Global Constraints for the Integration of Constraint Programming and Integer Programming. In Working Notes of the AAAI-2000 Workshop on Integration of AI and OR Techniques for Combinatorial Optimization.

    Google Scholar 

  120. Minton, S.; Bresina, J; and Drummond, M. 1994. Total-Order and PartialOrder Planning: A Comparative Analysis. Journal of Artificial Intelligence Research 2: 227–262.

    Google Scholar 

  121. Minton, S.; Johnston, M. D.; Philips, A. B.; and Laird, P. 1992. Minimizing Conflicts: a Heuristic Repair Method for Constraint Satisfaction and Scheduling Problems. Artificial Intelligence 58: 161–205.

    Article  MATH  MathSciNet  Google Scholar 

  122. Mittal, S., and Falkenhainer, B. 1990. Dynamic Constraint Satisfaction Problems. In Proceedings of the Eighth National Conference on Artificial Intelligence (AAAI-90), 25–32.

    Google Scholar 

  123. Mohr, R., and Henderson, T. C. 1986. Arc and Path Consistency Revisited. Artificial Intelligence 28(2): 225–233.

    Article  Google Scholar 

  124. Muscettola, N. 1994. HSTS: Integrating Planning and Scheduling. In Zweben, M., and Fox, M. S. (eds.), Intelligent Scheduling, Morgan Kaufmann, 169–212.

    Google Scholar 

  125. Muslea, I. 1998. A General-Purpose AI Planning System Based on the Genetic Programming Paradigm. In Proceedings of the World Automation Congress (WAC’98).

    Google Scholar 

  126. Myers, K. L. 1999. CPEF-A Continuous Planning and Execution Framework. AI Magazine 20(4): 63–69.

    Google Scholar 

  127. Nareyek, A. 1997. Constraint-based Agents. In Papers from the 1997 AAAI Workshop on Constraints & Agents, Technical Report, WS-97-05, 45–50. AAAI Press, Menlo Park, California.

    Google Scholar 

  128. Nareyek, A. 1998. A Planning Model for Agents in Dynamic and Uncertain Real-Time Environments. In Proceedings of the Workshop on Integrating Planning, Scheduling and Execution in Dynamic and Uncertain Environments at the Fourth International Conference on Artificial Intelligence Planning Systems (AIPS’98), Technical Report, WS-98-02, 7–14. AAAI Press, Menlo Park, California.

    Google Scholar 

  129. Nareyek, A. 1998. Constraint-basierte Planung für Agenten in Computerspielen. In Proceedings of the Workshop on Deklarative KI-Methoden zur Implementierung und Nutzung von Systemen in Netzen at the 22. Jahrestagung Künstliche Intelligenz (KI-98), 21–30.

    Google Scholar 

  130. Nareyek, A. 1999. Structural Constraint Satisfaction. In Papers from the 1999 AAAIWorkshop on Configuration, Technical Report, WS-99-05, 76–82. AAAI Press, Menlo Park, California.

    Google Scholar 

  131. Nareyek, A. 1999. Applying Local Search to Structural Constraint Satisfaction. In Proceedings of the IJCAI-99 Workshop on Intelligent Workflow and Process Management: The New Frontier for AI in Business.

    Google Scholar 

  132. Nareyek, A. 2000. AI Planning in a Constraint Programming Framework. In Hommel, G. (ed.), Communication-Based Systems, Kluwer Academic Publishers, 163–178.

    Google Scholar 

  133. Nareyek, A. 2000. Open World Planning as SCSP. In Papers from the AAAI2000 Workshop on Constraints and AI Planning, Technical Report, WS-00-02, 35–46. AAAI Press, Menlo Park, California.

    Google Scholar 

  134. Nareyek, A. 2000. Intelligent Agents for Computer Games. In Proceedings of the Second International Conference on Computers and Games (CG 2000), to appear.

    Google Scholar 

  135. Nareyek, A. 2000. Constraint Programming for Computer Games: Mastering “Real”-World Requirements. In Proceedings of the Thirteenth International Conference on Applications of Prolog (INAP 2000).

    Google Scholar 

  136. Nareyek, A. 2001. Using Global Constraints for Local Search. In Freuder, E. C., and Wallace, R. J. (eds.), Constraint Programming and Large Scale Discrete Optimization, American Mathematical Society Publications, DIMACS Volume 57.

    Google Scholar 

  137. Nareyek, A., and Geske, U. 1996. Efficient Representation of Relations over Linear Constraints. In Proceedings of the Workshop on Constraint Programming Applications at the Second International Conference on Principles and Practice of Constraint Programming (CP96), 55–63.

    Google Scholar 

  138. Nau, D.; Cao, Y.; Lotem, A.; and Muñoz-Avila, H. 1999. SHOP: Simple Hierarchical Ordered Planner. In Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence (IJCAI-99), 968–973.

    Google Scholar 

  139. Nemhauser, G. L. and Wolsey, L. A. 1988. Integer and Combinatorial Optimization. Reading, John Wiley & Sons, Inc.

    Google Scholar 

  140. Nievergelt, J.; Gasser, R.; Maser, F.; and Wirth, C. 1995. All the Needles in a Haystack: Can Exhaustive Search Overcome Combinatorial Chaos? In van Leeuwen, J. (ed.), Computer Science Today, Springer LNCS, 254–274.

    Chapter  Google Scholar 

  141. Nuijten, W. P. M. 1994. Time and Resource Constrained Scheduling: A Constraint Satisfaction Approach. PhD Thesis, Eindhoven University of Technology, Eindhoven, The Netherlands.

    MATH  Google Scholar 

  142. Oddi, A., and Smith, S. 1997. Stochastic Procedures for Generating Feasible Schedules. In Proceedings of the Fourteenth National Conference on Artificial Intelligence (AAAI-97), 308–314.

    Google Scholar 

  143. Paredis, J. 1999. Coevolutionary Algorithms. In Bäck, T.; Fogel, D.; and Michalewicz, Z. (eds.), The Handbook of Evolutionary Computation, 1st supplement, Oxford University Press.

    Google Scholar 

  144. Paolucci, M.; Kalp, D.; Pannu, A.; Shehory, O.; and Sycara, K. 1999. A Planning Component for RETSINA Agents. In Wooldridge, M., and Lesperance, Y. (eds.), Intelligent Agents VI, Springer LNAI.

    Google Scholar 

  145. Pell, B.; Bernard, D. E.; Chien, S. A.; Gat, E.; Muscettola, N.; Nayak, P. P.; Wagner, M. D.; and Williams, B. C. 1996. A Remote Agent Prototype for Spacecraft Autonomy. In Proceedings of the SPIE Conference on Optical Science, Engineering, and Instrumentation.

    Google Scholar 

  146. Penberthy, J. S., and Weld, D. S. 1992. UCPOP: A Sound, Complete, Partial Order Planner for ADL. In Proceedings of the Third International Conference on Principles of Knowledge Representation and Reasoning (KR’92), 102–114.

    Google Scholar 

  147. Penberthy, J. S., and Weld, D. S. 1994. Temporal Planning with Continuous Change. In Proceedings of the Twelfth National Conference on Artificial Intelligence (AAAI-94), 1010–1015.

    Google Scholar 

  148. Peot, M., and Smith, D. 1992. Conditional Nonlinear Planning. In Proceedings of the First International Conference on AI Planning Systems, 189–197.

    Google Scholar 

  149. Pesant, G., and Gendreau, M. 1999. A Constraint Programming Framework for Local Search Methods. Journal of Heuristics 5(3): 255–279.

    Article  MATH  Google Scholar 

  150. Prosser, P. 1993. Hybrid Algorithms for the Constraint Satisfaction Problem. Computational Intelligence 9(3): 268–299.

    Article  Google Scholar 

  151. Pryor, L., and Collins, G. 1996. Planning for Contingencies: A Decision-based Approach. Journal of Artificial Intelligence Research 4: 287–339.

    Google Scholar 

  152. Puget, J.-F., and Leconte, M. 1995. Beyond the Glass Box: Constraints as Objects. In Proceedings of the 1995 International Logic Programming Symposium (ILPS’95), 513–527.

    Google Scholar 

  153. Rabideau, G.; Chien, S.; Willis, J.; and Mann, T. 1999. Using Iterative Repair to Automate Planning and Scheduling of Shuttle Payload Operations. In Proceedings of the Eleventh Annual Conference on Innovative Applications of Artificial Intelligence (IAAI-99), 813–820.

    Google Scholar 

  154. Rabideau, G.; Knight, R.; Chien, S.; Fukunaga, A.; and Govindjee, A. 1999. Iterative Repair Planning for Spacecraft Operations in the ASPEN System. International Symposium on Artificial Intelligence Robotics and Automation in Space (iSAIRAS 99).

    Google Scholar 

  155. Règin, J.-C. 1998. Minimization of the Number of Breaks in Sports Scheduling Problems using Constraint Programming. In Proceedings of the DIMACS Workshop on Constraint Programming and Large Scale Discrete Optimization, P7: 1–23.

    Google Scholar 

  156. Reticular Systems, Inc. 1999. AgentBuilder-An Integrated Toolkit for Constructing Intelligent Software Agents. White Paper, Revision 1.3. Reticular Systems, Inc., Dan Diego, CA.

    Google Scholar 

  157. Rintanen, J., and Jungholt, H. 1999. Numeric State Variables in Constraintbased Planning. In Proceedings of the Fifth European Conference on Planning (ECP-99).

    Google Scholar 

  158. Rozenberg, G. ed. 1997. The Handbook of Graph Grammars. Volume I: Foundations. Reading, World Scientific.

    Google Scholar 

  159. Sabin, D., and Freuder, E. C. 1996. Configuration as Composite Constraint Satisfaction. In Proceedings of the Artificial Intelligence and Manufacturing Research Planning Workshop, 153–161.

    Google Scholar 

  160. Sacerdoti, E. D. 1974. Planning in a Hierarchy of Abstraction Spaces. Artificial Intelligence 5(2): 115–135.

    Article  MATH  Google Scholar 

  161. Sacerdoti, E. D. 1975. The Nonlinear Nature of Plans. In Proceedings of the Fourth International Joint Conference on Artificial Intelligence (IJCAI-75), 206–214.

    Google Scholar 

  162. Sadeh, N., and Fox, M. 1996. Variable and Value Ordering Heuristics for the Job Shop Scheduling Constraint Satisfaction Problem. Artificial Intelligence 86: 1–41.

    Article  Google Scholar 

  163. Schrag, R; Boddy, M; and Carciofini, J. 1992. Managing Disjunction for Practical Temporal Reasoning. In Proceedings of the Third International Conference on Principles of Knowledge Representation and Reasoning (KR’92), 36–46.

    Google Scholar 

  164. Schuurmans, D., and Southey, F. 2000. Local search characteristics of incomplete SAT procedures. In Proceedings of the Seventeenth National Conference on Artificial Intelligence (AAAI-2000), 297–302.

    Google Scholar 

  165. Selman, B.; Levesque, H.; and Mitchell, D. 1992. A New Method for Solving Hard Satisfiability Problems. In Proceedings of the Tenth National Conference on Artificial Intelligence (AAAI-92), 440–446.

    Google Scholar 

  166. Selman, B.; Kautz, H.; and Cohen, B. 1996. Local Search Strategies for Satisfiability Testing. In Johnson, D. S., and Trick, M. A. (eds.), Cliques, Coloring, and Satisfiability, DIMACS Volume 26: 521–532.

    Google Scholar 

  167. Smith, S. F. 1994. OPIS: A Methodology and Architecture for Reactive Scheduling. In Zweben, M., and Fox, M. S. (eds.), Intelligent Scheduling, Morgan Kaufmann, 29–66.

    Google Scholar 

  168. Sqalli, M. H.; Purvis, L.; and Freuder, E. C. 1999. Survey of Applications Integrating Constraint Satisfaction and Case-Based Reasoning. In Proceedings of the First International Conference and Exhibition on the Practical Application of Constraint Technologies and Logic Programming (PACLP99).

    Google Scholar 

  169. Srivastava, B., and Kambhampati, S. 1999. Scaling up Planning by teasing out Resource Scheduling. In Proceedings of the Fifth European Conference on Planning (ECP-99).

    Google Scholar 

  170. Stern, A.; Frank, A.; and Resner, B. 1998. Virtual Petz: A Hybrid Approach to Creating Autonomous Lifelike Dogz and Catz. In Proceedings of the Second International Conference on Autonomous Agents (AGENTS98), 334–335.

    Google Scholar 

  171. Stern, A. 1999. AI Beyond Computer Games. 1999 AAAI Symposium on Computer Games and Artificial Intelligence.

    Google Scholar 

  172. Tate, A. 1977. Generating Project Networks. In Proceedings of the Fifth International Joint Conference on Artificial Intelligence (IJCAI-77), 888–893.

    Google Scholar 

  173. Tumer, K., and Wolpert, D. 2000. Collective Intelligence and Braess’ Paradox. In Proceedings of the Seventeenth National Conference on Artificial Intelligence (AAAI-2000), 104–109.

    Google Scholar 

  174. Vaessens, R. J. M.; Aarts, E. H. L.; and Lenstra, J. K. 1994. Job Shop Scheduling by Local Search. Technical Report, COSOR Memorandum 94-05, Eindhoven University of Technology, Department of Mathematics and Computing Science.

    Google Scholar 

  175. Van Beek, P., and Chen, X. 1999. CPlan: A Constraint Programming Approach to Planning. In Proceedings of the Sixteenth National Conference on Artificial Intelligence (AAAI-99), 585–590.

    Google Scholar 

  176. Van Lent, M., and Laird, J. 1999. Developing an Artificial Intelligence Engine. In Proceedings of the 1999 Game Developers Conference (GDC 1999), 577–588.

    Google Scholar 

  177. Veloso, M.; Carbonell, J.; Pèrez, A.; Borrajo, D.; Fink, E.; and Blythe, J. 1995. Integrating Planning and Learning: The PRODIGY Architecture. Journal of Experimental and Theoretical Artificial Intelligence 7(1).

    Google Scholar 

  178. Veloso, M.; Muñoz-Avila, H.; and Bergmann, R. 1996. Case-based Planning: Selected Methods and Systems. AI Communications 9(3): 128–137.

    Google Scholar 

  179. Verfaillie, G., and Schiex, T. 1994. Solution Reuse in Dynamic Constraint Satisfaction Problems. In Proceedings of the Twelfth National Conference on Artificial Intelligence (AAAI-94), 307–312.

    Google Scholar 

  180. Vossen, T.; Ball, M.; Lotem, A.; and Nau, D. 1999. On the Use of Integer Programming Models in AI Planning. In Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence (IJCAI-99), 304–309.

    Google Scholar 

  181. Voudouris, C., and Tsang, E. 1995. Guided Local Search. Technical Report CSM-247, University of Essex, Department of Computer Science, Colchester, United Kingdom.

    Google Scholar 

  182. Waldinger, R. 1977. Achieving Several Goals Simultaneously. In Elcock, E., and Michie, D. (eds.), Machine Intelligence 8, Ellis Horwood Limited, 94–136.

    Google Scholar 

  183. Wallace, R. J., and Freuder, E. C. 1996. Anytime Algorithms for Constraint Satisfaction and SAT problems. SIGART Bulletin 7(2).

    Google Scholar 

  184. Wallace, R. J., and Freuder, E. C. 2000. Dispatchable execution of schedules involving consumable resources. In Proceedings of the Fifth International Conference on Artificial Intelligence Planning and Scheduling (AIPS-2000), 283–290.

    Google Scholar 

  185. Walser, J. P. 1997. Solving Linear Pseudo-Boolean Constraint Problems with Local Search. In Proceedings of the Fourteenth National Conference on Artificial Intelligence (AAAI-97), 269–274.

    Google Scholar 

  186. Warren, D. H. D. 1974. WARPLAN: A System for Generating Plans. Department of Computational Logic Memo 76, University of Edinburgh, Scotland.

    Google Scholar 

  187. Warren, D. H. D. 1976. Generating Conditional Plans and Programs. In Proceedings of the Summer Conference on Artificial Intelligence and Simulation on Behavior, 344–354.

    Google Scholar 

  188. Weizenbaum, J. 1966. ELIZA-A Computer Program for the Study of Natural Language Communication between Man and Machine. Communications of the ACM 9(1): 36–45.

    Article  Google Scholar 

  189. Wilkins, D. E.; Myers, K. L.; Lowrance, J. D.; and Wesley, L. P. 1995. Planning and Reacting in Uncertain and Dynamic Environments. Journal of Experimental and Theoretical AI 7(1): 197–227.

    Google Scholar 

  190. Williamson, M., and Hanks, S. 1994. Optimal Planning with a Goal-Directed Utility Model. In Proceedings of the Second International Conference on AI Planning Systems (AIPS-94), 176–181.

    Google Scholar 

  191. Wolfman, S. A., and Weld, D. S. 1999. The LPSAT Engine & its Application to Resource Planning. In Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence (IJCAI-99), 310–316.

    Google Scholar 

  192. Woodcock, S. 2000. Game AI: The State of the Industry. Game Developer, August 2000.

    Google Scholar 

  193. Wooldridge, M., and Jennings, N. R. 1995. Intelligent Agents: Theory and Practice. The Knowledge Engineering Review 10(2): 115–152.

    Article  Google Scholar 

  194. Wright, I., and Marshall, J. 2000. More AI in Less Processor Time: ‘Egocentric’ AI. Gamasutra, June 2000. http://www.gamasutra.com/features/20000619/wright_01.htm

  195. Zilberstein, S. 1996. Using Anytime Algorithms in Intelligent Systems. AI Magazine 17(3): 73–83.

    Google Scholar 

  196. Zweben, M.; Daun, B.; Davis, E.; and Deale, M. 1994. Scheduling and Rescheduling with Iterative Repair. In Zweben, M., and Fox, M. S. (eds.), Intelligent Scheduling, Morgan Kaufmann, 241–255.

    Google Scholar 

  197. Zwick, R., and Lee, C. C. 1999. Bargaining and search: An experimental study. Group Decision and Negotiation 8(6), 463–487.

    Article  Google Scholar 

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(2001). Ensuring the Satisfaction of Structural Constraints. In: Constraint-Based Agents. Lecture Notes in Computer Science(), vol 2062. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45746-1_11

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