Bibliography

1

F. Bacchus.
AIPS'00 Planning Competition.
AI Magazine, 22(3):47-56, 2001.

2

F. Bacchus and F. Kabanza.
Using Temporal Logics to Express Search Control Knowledge for Planning.
Artificial Intelligence, 16:123-191, 2000.

3

F. Bacchus and Q. Yang.
Downward Refinement and the Efficiency of Hierarchical Problem Solving.
Artificial Intelligence, 71(1):43-100, November 1994.

4

A. Botea, M. Müller, and J. Schaeffer.
Using Abstraction for Planning in Sokoban.
In J. Schaeffer, M. Müller, and Y. Björnsson, editors, 3rd International Conference on Computers and Games (CG'2002), volume 2883 of Lecture Notes in Artificial Intelligence, pages 360-375, Edmonton, Canada, July 2002. Springer.

5

A. Botea, M. Müller, and J. Schaeffer.
Near Optimal Hierarchical Path-Finding.
Journal of Game Development, 1(1):7-28, 2004.

6

A. Botea, M. Müller, and J. Schaeffer.
Using Component Abstraction for Automatic Generation of Macro-Actions.
In Fourteenth International Conference on Automated Planning and Scheduling ICAPS-04, pages 181-190, Whistler, Canada, June 2004. AAAI Press.

7

A. Coles and A. Smith.
Marvin: Macro Actions from Reduced Versions of the Instance.
In Booklet of the Fourth International Planning Competition, pages 24-26, June 2004.

8

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

9

M. Helmert.
A Planning Heuristic Based on Causal Graph Analysis.
In Fourteenth International Conference on Automated Planning and Scheduling ICAPS-04, pages 161-170, Whistler, Canada, June 2004.

10

I. Hernádvölgyi.
Searching for Macro-operators with Automatically Generated Heuristics.
In Fourteenth Canadian Conference on Artificial Intelligence, pages 194-203, 2001.

11

J. Hoffmann, S. Edelkamp, R. Englert, F. Liporace, S. Thiébaux, and S. Trüg.
Towards Realistic Benchmarks for Planning: the Domains Used in the Classical Part of IPC-4.
In Booklet of the Fourth International Planning Competition, pages 7-14, June 2004.

12

J. Hoffmann and B. Nebel.
The FF Planning System: Fast Plan Generation Through Heuristic Search.
Journal of Artificial Intelligence Research, 14:253-302, 2001.

13

Glenn A. Iba.
A Heuristic Approach to the Discovery of Macro-Operators.
Machine Learning, 3(4):285-317, 1989.

14

A. Junghanns and J. Schaeffer.
Sokoban: Enhancing Single-Agent Search Using Domain Knowledge.
Artificial Intelligence, 129(1-2):219-251, 2001.

15

S. Kambhampati.
Machine Learning Methods for Planning, chapter Supporting Flexible Plan Reuse, pages 397-434.
Morgan Kaufmann, 1993.

16

Craig A. Knoblock.
Automatically Generating Abstractions for Planning.
Artificial Intelligence, 68(2):243-302, 1994.

17

R. Korf.
Macro-Operators: A Weak Method for Learning.
Artificial Intelligence, 26(1):35-77, 1985.

18

J. Kvarnström and P. Doherty.
TALplanner: Temporal Logic Based Forward Chaining Planner.
Annals of Mathematics and Artificial Intelligence, 30:119-169, 2001.

19

D. Long and M. Fox.
The 3rd International Planning Competition: Results and Analysis.
Journal of Artificial Intelligence Research, 20:1-59, 2003.
Special Issue on the 3rd International Planning Competition.

20

T. Anthony Marsland.
A Review of Game-Tree Pruning.
International Computer Chess Association Journal, 9(1):3-19, 1986.

21

T. L. McCluskey and J. M. Porteous.
Engineering and Compiling Planning Domain Models to Promote Validity and Efficiency.
Artificial Intelligence, 95:1-65, 1997.

22

D. McDermott.
The 1998 AI Planning Systems Competition.
AI Magazine, 21(2):35-55, 2000.

23

S. Minton.
Selectively Generalizing Plans for Problem-Solving.
In IJCAI-85, pages 596-599, 1985.

24

S. Minton.
Learning Search Control Knowledge: An Explanation-Based Approach.
Hingham, MA, 1988. Kluwer Academic Publishers.

25

R. Mooney.
Generalizing the Order of Operators in Macro-Operators.
In Fifth International Conference on Machine Learning ICML-88, pages 270-283, June 1988.

26

D. Nau, T. Au, O. Ilghami, U. Kuter, J. Murdock, D. Wu, and F. Yaman.
SHOP2: An HTN Planning System.
Journal of Artificial Intelligence Research, 20:379-404, 2003.

27

E. Sacerdoti.
The Nonlinear Nature of Plans.
In Proceedings IJCAI-75, pages 206-214, 1975.

28

A. Tate.
Generating Project Networks.
In Proceedings of IJCAI-77, pages 888-893, 1977.

29

M. Veloso and J. Carbonell.
Machine Learning Methods for Planning, chapter Toward Scaling Up Machine Learning: A Case Study with Derivational Analogy, pages 233-272.
Morgan Kaufmann, 1993.

30

V. Vidal.
A Lookahead Strategy for Heuristic Search Planning.
In Fourteenth International Conference on Automated Planning and Scheduling ICAPS-04, pages 150-159, Whistler, Canada, June 2004.

31

D. Wilkins and M. desJardins.
A Call for Knowledge-Based Planning.
AI Magazine, 22(1):99-115, 2001.