AlphaZero – What’s Missing?

Abstract

In December 2017, the game playing program AlphaZero was reported to have learned in less than 24 hours to play each of the games of chess, Go and shogi better than any human, and better than any other existing specialised computer program for these games. This was achieved just by self-play, without access to any knowledge of these games other than the rules of the game. In this paper we consider some limitations to this spectacular success. The program was trained in well-defined and relatively small domains (admittedly with enormous combinatorial complexity) compared to many real world problems, and it was possible to generate large amounts of learning data through simulated games which is typically not possible in real life domains. When it comes to understanding the games played by AlphaZero, the program’s inability to explain its games and the knowledge acquired in human-understandable terms is a serious limitation.

Authors

  • Ivan Bratko University of Ljubljana, Faculty of Computer and Information Science

Downloads

Published

03/26/2018

How to Cite

Bratko, I. (2018). AlphaZero – What’s Missing?. Informatica, 42(1). Retrieved from https://www.informatica.si/index.php/informatica/article/view/2226

Issue

Vol. 42 No. 1 (2018)

Section

AI in Slovenia

License

Authors retain copyright in their work. By submitting to and publishing with Informatica, authors grant the publisher (Slovene Society Informatika) the non-exclusive right to publish, reproduce, and distribute the article and to identify itself as the original publisher.

All articles are published under the Creative Commons Attribution license CC BY 3.0. Under this license, others may share and adapt the work for any purpose, provided appropriate credit is given and changes (if any) are indicated.

Authors may deposit and share the submitted version, accepted manuscript, and published version, provided the original publication in Informatica is properly cited.