Abstract
We build a comprehensive macro-learning system and contribute in three different dimensions that have previously not been addressed adequately. Firstly, we learn macro-sets considering implicitly the interactions between constituent macros. Secondly, we effectively learn macros that are not found in given example plans. Lastly, we improve or reduce degradation of plan-length when macros are used; note, our main objective is to achieve fast planning. Our macro-learning system significantly outperforms a very recent macro-learning method both in solution speed and plan length.
Original language | English |
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Title of host publication | Proceedings of the 2010 conference on ECAI 2010 |
Subtitle of host publication | 19th European Conference on Artificial Intelligence |
Place of Publication | New York |
Pages | 323-328 |
Number of pages | 6 |
DOIs | |
Publication status | Published - 1 Aug 2010 |
Keywords
- artificial intelligence
- implicit learning