Crushing Candy Crush : Predicting Human Success Rate in a Mobile Game using Monte-Carlo Tree Search

The purpose of this thesis is to evaluate the possibility of predicting difficulty, measured in average human success rate (AHSR), across game levels of a mobile game using a general AI algorithm. ...

[1]  H. Jaap van den Herik,et al.  Single-Player Monte-Carlo Tree Search , 2008, Computers and Games.

[2]  Christopher D. Rosin,et al.  Nested Rollout Policy Adaptation for Monte Carlo Tree Search , 2011, IJCAI.

[3]  Alan Fern,et al.  Lower Bounding Klondike Solitaire with Monte-Carlo Planning , 2009, ICAPS.

[4]  Mark H. M. Winands,et al.  Beam Monte-Carlo Tree Search , 2012, 2012 IEEE Conference on Computational Intelligence and Games (CIG).

[5]  Simon M. Lucas,et al.  A Survey of Monte Carlo Tree Search Methods , 2012, IEEE Transactions on Computational Intelligence and AI in Games.

[6]  Hilmar Finnsson,et al.  Simulation-Based General Game Playing , 2012 .

[7]  Demis Hassabis,et al.  Mastering the game of Go with deep neural networks and tree search , 2016, Nature.

[8]  Guillaume Maurice Jean-Bernard Chaslot Chaslot,et al.  Monte-Carlo Tree Search , 2010 .

[9]  Donald E. Knuth,et al.  The Solution for the Branching Factor of the Alpha-Beta Pruning Algorithm , 1981, ICALP.

[10]  Guy Van den Broeck,et al.  Monte-Carlo Tree Search in Poker Using Expected Reward Distributions , 2009, ACML.

[11]  Tristan Cazenave,et al.  Nested Monte-Carlo Search , 2009, IJCAI.

[12]  Nils J. Nilsson,et al.  A Formal Basis for the Heuristic Determination of Minimum Cost Paths , 1968, IEEE Trans. Syst. Sci. Cybern..

[13]  Kyung-Joong Kim,et al.  Recent Advances in General Game Playing , 2015, TheScientificWorldJournal.

[14]  Eliezer Yudkowsky,et al.  The Ethics of Artificial Intelligence , 2014, Artificial Intelligence Safety and Security.

[15]  Peter Norvig,et al.  Artificial Intelligence: A Modern Approach , 1995 .

[16]  Shin-Ming Cheng,et al.  Technologies and Applications of Artificial Intelligence: 19th International Conference, TAAI 2014, Taipei, Taiwan, November 21-23, 2014, Proceedings , 2014 .

[17]  Daniel J. Fagnant,et al.  Preparing a Nation for Autonomous Vehicles: Opportunities, Barriers and Policy Recommendations , 2015 .

[18]  J. Neumann Zur Theorie der Gesellschaftsspiele , 1928 .

[19]  S. Schneider Science fiction and philosophy : from time travel to superintelligence , 2016 .

[20]  Toby Walsh Candy Crush is NP-hard , 2014, ArXiv.

[21]  Fabien Teytaud,et al.  Optimization of the Nested Monte-Carlo Algorithm on the Traveling Salesman Problem with Time Windows , 2011, EvoApplications.

[22]  Csaba Szepesvári,et al.  Bandit Based Monte-Carlo Planning , 2006, ECML.

[23]  Rémi Coulom,et al.  Efficient Selectivity and Backup Operators in Monte-Carlo Tree Search , 2006, Computers and Games.