AI Planning Group at University of Alberta: Publications

2013

H. Nakhost and M. Müller. Towards a second generation random walk planner: an experimental exploration. Accepted for IJCAI 2013. Acceptance rate 413/1473 = 28%. 7 pp.

F. Xie, R. Valenzano and M. Müller. Better time constrained search via randomization and postprocessing. Accepted for ICAPS, 2013.

F. Xie, R. Valenzano and M. Müller. Better time constrained search via randomization and postprocessing. Technical Report TR 13-02, Dept. of Computing Science. University of Alberta, Edmonton, Alberta, Canada, 2013.

2012

H. Nakhost and M. Müller. A Theoretical Framework for Studying Random Walk Planning. In SOCS, 2012.

R. Valenzano, H. Nakhost, M. Müller, J. Schaeffer, and N. Sturtevant. ArvandHerd: Parallel Planning with a Portfolio. In ECAI, 2012.

H. Nakhost, J. Hoffmann and M. Müller. Resource-Constrained Planning: A Monte Carlo Random Walk Approach. In ICAPS, 2012.

F. Xie, H. Nakhost and M. Müller. Planning via Random Walk-Driven Local Search. In ICAPS, 2012.

2011

R. Valenzano, H. Nakhost, M. Müller, J. Schaeffer, and N. Sturtevant. ArvandHerd: Parallel Planning with a Portfolio. 2011 International Planning Competition (IPC 2011) Planner Description Booklet.

H. Nakhost, M. Müller, R. Valenzano, and F. Xie. Arvand: the Art of Random Walks. 2011 International Planning Competition (IPC 2011) Planner Description Booklet.

F. Xie, H. Nakhost and M. Müller. A Local Monte Carlo Tree Search Approach in Deterministic Planning. AAAI Conference on Artificial Intelligence Student Abstract and Poster Program (SA-11), pages 1832-1833, 2011.

2010

H. Nakhost, J. Hoffmann and M. Müller. Improving Local Search for Resource-Constrained Planning. Extended abstract. Proceedings of the Third Annual Symposium on Combinatorial Search (SOCS-10), pages 81-82, Stone Mountain, Atlanta, GA, USA, 2010. Download from aaai.org

H. Nakhost and M. Müller. Action Elimination and Plan Neighborhood Graph Search: Two Algorithms for Plan Improvement, 2010. International Conference on Automated Planning and Scheduling (ICAPS-2010), pages 121-128, 2010. Editors R. Brafman, H. Geffner, J. Hoffmann and H. Kautz. AAAI Press, Toronto, Canada. Acceptance rate: 37/108 = 34%. Download from aaai.org

H. Nakhost and M. Müller. Action Elimination and Plan Neighborhood Graph Search: Two Algorithms for Plan Improvement - Extended Version, 2010. Technical report TR 10-01, Dept. of Computing Science. University of Alberta.

2009

H. Nakhost and M. Müller. Monte-Carlo exploration for deterministic planning, 2009. In Twenty-first International Joint Conference on Artificial Intelligence (IJCAI), pages 1766-1771, Pasadena, California, USA, 2009. Acceptance rate: 331/1290 = 26%. pdf

2002-2007

A. Botea, M. Müller, and J. Schaeffer. Fast planning with iterative macros. In Twentieth International Joint Conference on Artificial Intelligence (IJCAI), pages 1828-1833, Hyderabad, India, 2007. Acceptance rate (oral presentation): 212/1353 = 15.7%. pdf, 168k.

A. Botea. Improving AI Planning and Search with Automatic Abstraction. PhD thesis, University of Alberta, 2006. pdf.

A. Botea, M. Enzenberger, M. Müller, and J. Schaeffer. Macro-FF: Improving AI planning with automatically learned macro-operators. Journal of Artificial Intelligence Research, 24:581-621, 2005. Download from JAIR.

A. Botea, M. Müller, and J. Schaeffer. Learning partial-order macros from solutions. In S. Biundo, K. Myers, and K. Rajan, editors, ICAPS 2005. Proceedings of the 15th International Conference on Automated Planning and Scheduling, pages 231-240, Monterey, California, 2005. pdf, 484k.

A. Botea, M. Enzenberger, M. Müller, and J. Schaeffer. Macro-FF, 2004. In booklet of the International Planning Competition (IPC-4). http://ls5-www.cs.uni-dortmund.de/~edelkamp/ipc-4/IPC-4.pdf.

A. Botea, M. Müller, and J. Schaeffer. Using component abstraction for automatic generation of macro-actions. In S. Zilberstein, J. Koehler, and S. Koenig, editors, ICAPS 2004. Proceedings of the 14th International Conference on Automated Planning and Scheduling, pages 181-190, Whistler, Canada, 2004.

  • pdf, 183k.

    A. Botea, M. Müller, and J. Schaeffer. Using abstraction for planning in Sokoban. In J. Schaeffer, M. Müller, and Y. Björnsson, editors, Computers and Games 2002, number 2883 in Lecture Notes in Computer Science, pages 360-375. Springer Verlag, 2003.

  • pdf, 546k.

    A. Botea, M. Müller, and J. Schaeffer. Extending PDDL for hierarchical planning and topological abstraction. In iCAPS workshop on PDDL, pages 25-32, 2003.

    A. Botea. Reducing planning complexity with topological abstraction. Proceedings of the International Conference on Automated Planning & Scheduling (ICAPS-03) Doctoral Consortium, Trento, Italy, 2003.

    A. Botea. Using abstraction for heuristic search and planning. In S. Koenig and R. Holte, editors, 5th International Symposium on Abstraction, Reformulation, and Approximation, number 2371 in Lecture Notes in Computer Science, pages 326-327. Springer Verlag, 2002.


    Created: Apr 23, 2013 Last modified: Apr 23, 2013

    Planning Group