We apply Monte Carlo simulation and alpha-beta search to the card game of Skat, which is similar to Bridge, but different enough to require some new algorithmic ideas besides the t...
Abstract. The Monte-Carlo Tree Search algorithm has been successfully applied in various domains. However, its performance heavily depends on the Monte-Carlo part. In this paper, w...
Nested Monte-Carlo search is a general algorithm that gives good results in single player games. Genetic Programming evaluates and combines trees to discover expressions that maxim...
This paper describes a computationally feasible approximation to the AIXI agent, a universal reinforcement learning agent for arbitrary environments. AIXI is scaled down in two ke...
Joel Veness, Kee Siong Ng, Marcus Hutter, William ...
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. ...