Towards MCTS for Creative Domains
Inhaltsverzeichnis
Reference
Cameron Browne: Towards MCTS for Creative Domains. In: Computational Creativity 2011 ICCC 2011, pp. 96-101.
DOI
Abstract
Monte Carlo Tree Search (MCTS) has recently demon- strated considerable success for computer Go and other difficult AI problems. We present a general MCTS model that extends its application from searching for optimal actions in games and combinatorial optimisa- tion tasks to the search for optimal sequences and em- bedded subtrees. The primary application of this ex- tended MCTS model will be for creative domains, as it maps naturally to a range of procedural content genera- tion tasks for which Markovian or evolutionary ap- proaches would typically be used.
Extended Abstract
Bibtex
@inproceedings{
author = {Cameron Browne},
title = {Towards MCTS for Creative Domains},
editor = {Dan Ventura, Pablo Gervás, D. Fox Harrell, Mary Lou Maher, Alison Pease and Geraint Wiggins},
booktitle = {Proceedings of the Second International Conference on Computational Creativity},
series = {ICCC2011},
year = {2011},
month = {April},
location = {México City, México},
pages = {96-101},
url = {http://iccc11.cua.uam.mx/proceedings/the_foundational/browne_iccc11.pdf, http://de.evo-art.org/index.php?title=Towards_MCTS_for_Creative_Domains },
publisher = {International Association for Computational Creativity},
keywords = {computational, creativity},
}
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Links
Full Text
http://iccc11.cua.uam.mx/proceedings/the_foundational/browne_iccc11.pdf
