General game-playing systems

The aim of General Game Playing (GGP) is to create intelligent agents that can automatically learn how to play a wide variety of different games at an expert level without any human intervention. This requires that the agents be capable of learning diverse game-playing strategies from basic game rules without any game-specific knowledge being provided by their developers. A successful realization of this task poses interesting research challenges for artificial intelligence sub-disciplines such as knowledge representation, agent-based reasoning, heuristic search, computational intelligence, and machine learning. This talk gives an overview of the state-of-the-art of general game playing systems, including different design models, and discusses some open research challenges.