Details
Title
On transformation of conditional, conformant and parallel planning to linear programmingJournal title
Archives of Control SciencesYearbook
2021Volume
vol. 31Issue
No 2Affiliation
Galuszka, Adam : Department of Automatic Control and Robotics, Silesian University of Technology, Akademicka 16, 44-100 Gliwice, Poland ; Probierz, Eryka : Department of Automatic Control and Robotics, Silesian University of Technology, Akademicka 16, 44-100 Gliwice, PolandAuthors
Keywords
planning ; conformant planning ; conditional planning ; parallel planning ; uncertainty ; linear programming ; computational complexityDivisions of PAS
Nauki TechniczneCoverage
375-399Publisher
Committee of Automatic Control and Robotics PASBibliography
[1] J.L. Ambite and C.A. Knoblock: Planning by rewriting. Journal of Artificial Intelligence Research, 15 (2001), 207–261, DOI: 10.1613/jair.754.[2] Ch. Backstrom: Computational Aspects of Reordering Plans. Journal of Artificial Intelligence Research, 9 (1998), 99–137, DOI: 10.1613/jair.477.
[3] Ch. Baral, V. Kreinovich, and R. Trejo: Computational complexity of planning and approximate planning in the presence of incompleteness. Artificial Intelligence, 122 (2000), 241–267, DOI: 10.1007/3-540-44957-4_59.
[4] R. Bartak: Constraint satisfaction techniques in planning and scheduling: An introduction. Archives of Control Sciences, 18(2), (2008), DOI: 10.1007/s10845-008-0203-4.
[5] A. Bhattacharya and P. Vasant: Soft-sensing of level of satisfaction in TOC product-mix decision heuristic using robust fuzzy-LP, European Journal of Operational Research, 177(1), (2007), 55–70, DOI: 10.1016/j.ejor.2005.11.017.
[6] J. Blythe: An Overview of Planning Under Uncertainty. Pre-print from AI Magazine, 20(2), (1999), 37–54, DOI: 10.1007/3-540-48317-9_4.
[7] T. Bylander: The Computational Complexity of Propositional STRIPS Planning. Artificial Intelligence, 69 (1994), 165–204, DOI: 10.1016/0004- 3702(94)90081-7.
[8] T. Bylander: A Linear Programming Heuristic for Optimal Planning. In Proc. of AAAI Nat. Conf., (1997).
[9] L.G. Chaczijan: A polynomial algorithm for linear programming. Dokł. Akad. Nauk SSSR, 244 (1979), 1093–1096.
[10] E.R. Dougherty and Ch.R. Giardina: Mathematical Methods for Artificial Intelligence and Autonomous Systems, Prentice-Hall International, Inc. USA, 1988.
[11] I. Elamvazuthi, P. Vasant, and T. Ganesan: Fuzzy Linear Programming using Modified Logistic Membership Function, International Review of Automatic Control, 3(4), (2010), 370–377, DOI: 10.3923/jeasci.2010.239.245.
[12] A. Galuszka: On transformation of STRIPS planning to linear programming. Archives of Control Sciences, 21(3), (2011), 227–251, DOI: 10.2478/v10170-010-0042-3.
[13] A. Galuszka, W. Ilewicz, and A. Olczyk: On Translation of Conformant Action Planning to Linear Programming. Proc. 20th International Conference on Methods and Models in Automation & Robotics, 24–27 August, (2005), 353–357, DOI: 10.1109/MMAR.2015.7283901.
[14] A. Galuszka, T. Grzejszczak, J. Smieja, A. Olczyk, and J. Kocerka: On parallel conformant planning as an optimization problem. 32nd Annual European Simulation and Modelling Conference, Ghent, (2018), 17–22.
[15] M. Ghallab et al.: PDDL – the Planning Domain Definition Language, Version 1.2. Technical Report DCS TR-1165, Yale Center for Computational Vision and Control, (1998).
[16] A. Grastien and E. Scala: Sampling Strategies for Conformant Planning. Proc. Twenty-Eighth International Conference on Automated Planning and Scheduling, (2018), 97–105.
[17] A. Grastien and E. Scala: CPCES: A planning framework to solve conformant planning problems through a counterexample guided refinement. Artificial Intelligence, 284 (2020), 103271, DOI: 10.1016/j.artint.2020.103271.
[18] D. Hoeller, G. Behnke, P. Bercher, S. Biundo, H. Fiorino, D. Pellier, and R. Alford: HDDL: An extension to PDDL for expressing hierarchical planning problems. Proc. AAAI Conference on Artificial Intelligence, 34(6), (2020), 1–9, DOI: 10.1609/aaai.v34i06.6542.
[19] J. Koehler and K. Schuster: Elevator Control as a Planning Problem. AIPS-2000, (2000), 331–338.
[20] R. van der. Krogt: Modification strategies for SAT-based plan adaptation. Archives of Control Sciences, 18(2), (2008).
[21] M.D. Madronero, D. Peidro, and P. Vasant: Vendor selection problem by using an interactive fuzzy multi-objective approach with modified s-curve membership functions. Computers and Mathematics with Applications, 60 (2010), 1038–1048, DOI: 10.1016/j.camwa.2010.03.060.
[22] A. Nareyek, C. Freuder, R. Fourer, E. Giunchiglia, R.P. Goldman, H. Kautz, J. Rintanen, and A. Tate: Constraitns and AI Planning. IEEE Intelligent Systems, (2005), 62–72, DOI: 10.1109/MIS.2005.25.
[23] N.J. Nilson: Principles of Artificial Intelligence. Toga Publishing Company, Palo Alto, CA, 1980.
[24] E.P.D. Pednault: ADL and the state-transition model of action. Journal of Logic and Computation, 4(5), (1994), 467–512, DOI: 10.1093/logcom/4.5.467.
[25] D. Peidro and P. Vasant: Transportation planning with modified scurve membership functions using an interactive fuzzy multi-objective approach, Applied Soft Computing, 11 (2011), 2656–2663, DOI: 10.1016/j.asoc.2010.10.014.
[26] F. Pommerening, G. Roger, M. Helmert, H. Cambazard, L.M. Rousseau, and D. Salvagnin: Lagrangian decomposition for classical planning. Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, (2020), 4770—4774, DOI: 10.24963/ijcai. 2020/663.
[27] T. Rosa, S. Jimenez, R. Fuentetaja, and D. Barrajo: Scaling up heuristic planning with relational decision trees. Journal of Artificial Intelligence Research, 40 (2011), 767–813, DOI: 10.1613/jair.3231.
[28] S.J. Russell and P. Norvig: Artificial Intelligence: A Modern Approach. Fourth Edition. Pearson, 2020.
[29] J. Seipp, T. Keller, and M. Helmert: Saturated post-hoc optimization for classical planning. Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, (2021).
[30] D.E. Smith and D.S. Weld: Conformant Graphplan. Proc. 15th National Conf. on AI, (1998).
[31] D.S. Weld: Recent Advantages in AI Planning. AI Magazine, (1999), DOI: 10.1609/aimag.v20i2.1459.
[32] D.S. Weld, C.R. Anderson, and D.E. Smith: Extending graphplan to handle uncertainty & sensing actions. Proc. 15th National Conf. on AI, (1998), 897–904.
[33] X. Zhang, A. Grastien, and E. Scala: Computing superior counterexamples for conformant planning. Proc. AAAI Conference on Artificial Intelligence 34(6), (2020), 1–8, DOI: 10.1609/aaai.v34i06.6558.