- author = "Achiya Elyasaf and Ami Hauptman and Moshe Sipper",
- title = "Evolutionary Design of {FreeCell} Solvers",
- journal = "IEEE Transactions on Computational Intelligence and AI in Games",
- year = "2012",
- volume = "4",
- month = dec,
- pages = "270--281",
- keywords = "genetic algorithms, genetic programming, GAs, GP, artificial intelligence, computer games, search problems, FreeCell solver, Microsoft 32 K problem set, building blocks, evolutionary design, evolutionary setup, genetic algorithm, heuristic measure, human-challenging puzzle, minimal domain knowledge, policy-based genetic programming, search node, solution length, solution time, staged deepening search, Games, Heuristic algorithms, Learning systems, Planning, Search problems, Standards, Evolutionary algorithms, heuristic, hyperheuristic",
-
DOI = "
doi:10.1109/TCIAIG.2012.2210423",
-
URL = "
http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6249736",
- ISSN = "1943-068X",
- size = "12 pages",
- abstract = "In this paper, we evolve heuristics to guide staged deepening search for the hard game of FreeCell, obtaining top-notch solvers for this human-challenging puzzle. We first devise several novel heuristic measures using minimal domain knowledge and then use them as building blocks in two evolutionary setups involving a standard genetic algorithm and policy-based, genetic programming. Our evolved solvers outperform the best FreeCell solver to date by three distinct measures: 1) number of search nodes is reduced by over 78percent; 2) time to solution is reduced by over 94percent; and 3) average solution length is reduced by over 30percent. Our top solver is the best published FreeCell player to date, solving 99.65percent of the standard Microsoft 32 K problem set. Moreover, it is able to convincingly beat high-ranking human players.",
-
notes = "Entered 2012 Humies. Joint winner 2013 HUMIES GECCO
2013
Broken March 2021 http://tech.groups.yahoo.com/group/genetic_programming/message/6219
Also known as \cite{6249736} \cite{Elyasaf2012}",
