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.
|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|
|Number of pages||6|
|Publication status||Published - 1 Aug 2010|
- artificial intelligence
- implicit learning