@inproceedings{8a86531222b34aceb56dd1a655b26887,
title = "An investigation into 2048 AI strategies",
abstract = "2048 is a recent stochastic single player game, originally written in JavaScript for playing in a web browser but now largely played on mobile devices [1]. This paper discusses the applicability of Monte-Carlo Tree-Search (MCTS) to the problem, and also Averaged Depth Limited Search (ADLS). While MCTS plays reasonably well for a player with no domain knowledge, the ADLS player fares much better given an evaluation function that rewards board properties. Attempts to guide the roll-outs of MCTS using an evaluation function proved fruitless.",
keywords = "artificial intelligence, Monte Carlo methods, tree searching, computer games",
author = "Philip Rodgers and John Levine",
note = "Changed template from conference paper 6/02/2020 ",
year = "2014",
month = oct,
day = "23",
doi = "10.1109/CIG.2014.6932920",
language = "English",
isbn = "9781479935468",
publisher = "IEEE",
booktitle = "2014 IEEE Conference on Computational Intelligence and Games",
}