Szczegóły

Tytuł artykułu

On transformation of STRIPS planning to linear programming

Tytuł czasopisma

Archives of Control Sciences

Rocznik

2011

Numer

No 3

Autorzy

Wydział PAN

Nauki Techniczne

Wydawca

Committee of Automatic Control and Robotics PAS

Data

2011

Identyfikator

DOI: 10.2478/v10170-010-0042-3 ; ISSN 1230-2384

Źródło

Archives of Control Sciences; 2011; No 3

Referencje

Ambite J. (2001), Planning by rewriting, J. of Artificial Intelligence Research, 15, 207. ; Avriel M. (1998), Stowage planning for container ships to reduce the number of shifts, Annals of Operations Research, 76, 55, doi.org/10.1023/A:1018956823693 ; Backstrom Ch. (1998), Computational aspects of reordering plans, J. of Artificial Intelligence Research, 9, 99. ; Baral Ch. (2000), Computational complexity of planning and approximate planning in the presence of incompleteness, Artificial Intelligence, 122, 241, doi.org/10.1016/S0004-3702(00)00043-6 ; Bartak R. (2008), Constraint satisfaction techniques in planning and scheduling: An introduction, Archives of Control Sciences, 18, 2. ; Bhattacharya A. (2007), Soft-sensing of level of satisfaction in TOC product-mix decision heuristic using robust fuzzy-LP, European J. of Operational Research, 177, 1, 55, doi.org/10.1016/j.ejor.2005.11.017 ; Bish E. (2001), Analysis of a new vehicle scheduling and location problem, Naval Research Logistics, 48, 363, doi.org/10.1002/nav.1024 ; Blythe J. (1999), An overview of planning under uncertainty, Pre-print from AI Magazine, 20, 2, 37. ; Boutilier C. (2001), 2001. Partial-order planning with concurrent interacting actions, J. of Artificial Intelligence Research, 14, 105. ; Bylander T. (1994), The computational complexity of propositional STRIPS planning, Artificial Intelligence, 69, 165, doi.org/10.1016/0004-3702(94)90081-7 ; Bylander T. (1997), A linear programming heuristic for optimal planning, null. ; Chaczijan L. (1979), A polynomial algorithm for linear programming, Dokl. Akad. Nauk SSSR, 244, 1093. ; Dougherty E. (1988), Mathematical methods for artificial intelligence and autonomous systems. ; Elamvazuthi I. (2010), Fuzzy linear programming using modified logistic membership function, Int. Review of Automatic Control (IREACO), 3, 4, 370. ; A. Galuszka and A. Swierniak: Translation STRIPS planning in multi-robot environment to linear programming. <i>ICAISC 2004 (LNCS 3070)</i>, (2004), 768-773. ; Galuszka A. (2010), Planning in multi-agent environment using strips representation and non-cooperative equilibrium strategy, J. of Intelligent and Robotic Systems, 58, 3, 239, doi.org/10.1007/s10846-009-9364-4 ; Galuszka A. (2006), Artificial intelligence and soft computing, 389. ; A. Galuszka: Scoring functions of approximation of STRIPS planning by linear programming. In Simulation, Modelling and Optimization. Mathematics and Computers in Science and Engineering. A series of Reference Books and Text-books (Eds. I. Rudas <i>et al</i>.), ISBN 978-960-474-113-7, 2009, 316-321. ; M Ghallab (1998), PDDL - the planning domain definition language. Version 1.2. ; Imai A. (2001), The dynamic berth allocation problem for a container port, Transportation Research B, 35, 401, doi.org/10.1016/S0191-2615(99)00057-0 ; Koehler J. (2000), On reasonable and forced goal orderings andtheir Use in an agenda-driven planning algorithm, J. of Artificial Intelligence Research, 12, 339. ; Koehler J. (2000), Elevator control as a planning problem, AIPS-2000, 331. ; Kraus S. (1998), Reaching agreements through argumentation: a logical model and implementation, Artificial Intelligence, 104, 1, doi.org/10.1016/S0004-3702(98)00078-2 ; R. van der Krogt (2008), Modification strategies for SAT-based plan adaptation, Archives of Control Sciences, 18, 2. ; Madronero M. (2010), Vendor selection problem by using an interactive fuzzy multi-objective approach with modified s-curve membership functions, Computers and Mathematics with Applications, 60, 1038, doi.org/10.1016/j.camwa.2010.03.060 ; Nareyek A. (2005), Constraitns and AI planning, IEEE Intelligent Systems, 62, doi.org/10.1109/MIS.2005.25 ; Nilson N. (1980), Principles of artificial intelligence. ; Pednault E. (1994), ADL and the state-transition model of action, J. of Logic and Computation, 4, 5, 467, doi.org/10.1093/logcom/4.5.467 ; Peidro D. (2011), Transportation planning with modified s-curve membership functions using an interactive fuzzy multi-objective approach, Applied Soft Computing, 11, 2656, doi.org/10.1016/j.asoc.2010.10.014 ; Rosa T. (2011), Scaling up heuristic planning with relational decision trees, J. of Artificial Intelligence Research, 40, 767. ; Russell S. (2003), Artificial intelligence: A modern approach. ; Slaney J. (2001), Block world revisited, Artificial Intelligence, 125, 119, doi.org/10.1016/S0004-3702(00)00079-5 ; Slavin T. (1996), Virtual port of call, New Scientist, 40. ; Smith D. (1998), Conformant graphplan, null. ; Weld D. (1999), Recent advantages in AI planning, AI Magazine. ; Weld D. (1998), Extending graphplan to handle uncertainty and sensing actions, null, 897. ; Wilson I. (2000), Container stowage planning: a methodology for generating computerised solutions, J. of the Operational Research Society, 51, 1248, doi.org/10.1057/palgrave.jors.2601022 ; Zhang Y. (1995), Solving large-scale linear programs by interior-point methods under the MATLAB Environment.

Polityka Open Access

Archives of Control Sciences is an open access journal with all content available with no charge in full text version.


The journal content is available under the licencse CC BY-NC-ND 4.0 https://creativecommons.org/licenses/by-nc-nd/4.0/.
×