Games have played a prominent role as a test-bed for advancements in the field of Artificial
Intelligence ever since its foundation over half a century ago, resulting in highly specialized …

The aim of General Game Playing (GGP) is to create intelligent agents that automatically
learn how to play many different games at an expert level without any human intervention …

Effective search control is one of the key components of any successful simulation-based
game-playing program. In General Game Playing (GGP), learning of useful search-control …

Abstract We present the General Game Playing system Centurio. Centurio is a Java-based
player featuring different strategies based on Monte Carlo Tree Search extended by …

Search is an important topic in many areas of AI. Search problems often result in an
immense number of states. This work addresses this by using a special datastructure, BDDs …

Move pruning is a low-overhead technique for reducing search cost in single-agent search
problems by avoiding the generation of duplicate states. Redundant sequences of moves …

We present a general approach for the decomposition of games described in the Game
Description Language (GDL). In the field of General Game Playing, the exploration of games …

Abstract Research in General Game Playing aims at building systems that learn to play
unknown games without human intervention. We contribute to this endeavour by …

Although we humans cannot compete with computers at simple brute-force search, this is
often more than compensated for by our ability to discover structures in new games and to …

General game players can drastically reduce the cost of search if they are able to solve
smaller subproblems individually and synthesise the resulting solutions. To provide a …