Measuring Intelligence through Games

Abstract Artificial general intelligence (AGI) refers to research aimed at tackling the full problemof artificial intelligence, that is, create truly intelligent agents. This sets it apart from mostAI research which aims at solving relatively narrow domains, such as character recognition,motion planning, or increasing player satisfaction in games. But how do we know when anagent is truly intelligent? A common point of reference in the AGI community is Legg andHutter’s formal definition of universal intelligence, which has the appeal of simplicity andgenerality but is unfortunately incomputable.Games of various kinds are commonly used as benchmarks for “narrow” AI research,as they are considered to have many important properties. We argue that many of theseproperties carry over to the testing of general intelligence as well. We then sketch how suchtesting could practically be carried out. The central part of this sketch is an extension ofuniversal intelligence to deal with finite time, and the use of sampling of the space of gamesexpressed in a suitably biased game description language.Keywords: measure of intelligence, games

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