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.
| Original language | English |
|---|---|
| Title of host publication | 2014 IEEE Conference on Computational Intelligence and Games |
| Publisher | IEEE |
| Number of pages | 2 |
| ISBN (Electronic) | 9781479935475 |
| ISBN (Print) | 9781479935468 |
| DOIs | |
| Publication status | Published - 23 Oct 2014 |
| Event | 2014 IEEE Conference on Computational Intelligence and Games - Dortmund, Germany Duration: 26 Aug 2014 → 29 Aug 2014 http://www.cig2014.de/ |
Publication series
| Name | IEEE Conference on Computatonal Intelligence and Games, CIG |
|---|---|
| ISSN (Print) | 2325-4270 |
| ISSN (Electronic) | 2325-4289 |
Conference
| Conference | 2014 IEEE Conference on Computational Intelligence and Games |
|---|---|
| Abbreviated title | CIG2014 |
| Country/Territory | Germany |
| City | Dortmund |
| Period | 26/08/14 → 29/08/14 |
| Internet address |
Keywords
- artificial intelligence
- Monte Carlo methods
- tree searching
- computer games
ASJC Scopus subject areas
- Software
- Artificial Intelligence
- Human-Computer Interaction
- Computer Vision and Pattern Recognition
- Computer Graphics and Computer-Aided Design