Merge-and-Shrink Heuristics for AI Planning

Merge-and-Shrink is Gaojian Fan's PhD topic.

G. Fan. Understanding and Improving Merge-and-Shrink Abstraction for Cost Optimal Planning. PhD thesis, University of Alberta, 2019.

G. Fan, R. Holte and M. Müller. MS-lite: A Lightweight, Complementary Merge-and-Shrink Method.
In ICAPS 2018, pages 74-82. Delft, The Netherlands, 2018.

G. Fan, R. Holte and M. Müller. Additive merge-and-shrink heuristics for diverse action costs. IJCAI 2017, 4287-4293.

G. Fan, M. Müller and R. Holte. The two-edged nature of diverse action costs. ICAPS 2017, 98-106.

G. Fan. Diverse Action Costs in Heuristic Search and Planning. In AI 2017: Advances in Artificial Intelligence, Springer LNCS 10233, 399-402, 2017.

G. Fan, M. Müller and R. Holte. Non-Linear Merging Strategies for Merge-and-Shrink Based on Variable Interactions. SOCS, p. 53-61, 2014.


Created: Aug 21, 2019 Last modified: Aug 21, 2019
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