In general, games pose interesting and complex problems for the implementation of
intelligent agents and are a popular domain in the study of artificial intelligence. In fact …

Abstract In 1950, Claude Shannon published his seminal work on how to program a
computer to play chess. Since then, developing game-playing programs that can compete …

The temporal difference (TD) learning algorithm offers the hope that the arduous task of
manually tuning the evaluation function weights of game-playing programs can be …

This paper presents a new method, Minimax Tree Optimization (MMTO), to learn a heuristic
evaluation function of a practical alpha-beta search program. The evaluation function may …

Software models are increasingly popular. To educate the next generation of software
engineers, it is important that they learn how to model software systems well, so that they …

The game of poker offers a clean well-defined domain in which to investigate some truly
fundamental issues in computing science, such as how to handle deliberate misinformation …

In recent years, the field of artificial intelligence (AI) has witnessed remarkable progress and
its applications have extended to the realm of video games. The incorporation of AI in video …

This paper describes experiments using reinforcement learning techniques to compute
pattern urgencies used during simulations performed in a Monte-Carlo Go architecture …

Humans and machines are very different in their approaches to game playing. Humans use
intuition, perception mechanisms, selective search, creativity, abstraction, heuristic abilities …

A study was conducted to find out how game-playing strategies for Othello (also known as
reversi) can be learned without expert knowledge. The approach used the coevolution of a …