Abstract Monte Carlo Tree Search (MCTS) is a powerful approach to designing game-
playing bots or solving sequential decision problems. The method relies on intelligent tree …

1.1 Background Modern Artificial Intelligence (AI) research began in the mid-1950s [1].
Mainstream AI scientists focused on the narrow AI research which usually aims to solve a …

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 …

In the process of polyphonic music creation, it is important to combine two or more
independent melodies through technical treatment. However, due to the diversity of …

Applying latent variable evolution to game level design has become more and more popular
as little human expert knowledge is required. However, defective levels with illegal patterns …

Procedural Content Generation is an active area of research, with more interest being given
recently to methods able to produce interesting content in a general context (without task …

Intelligent game agents are crafted using AI technologies to mimic player behavior and
make decisions autonomously. Over the past decades, the scope of intelligent agents has …

Abstract Research in Artificial Intelligence has shown that machines can be programmed to
perform as well as, or even better than humans in specific tasks, such as playing Chess …

Game-based benchmarks have been playing an essential role in the development of
Artificial Intelligence (AI) techniques. Providing diverse challenges is crucial to push …

Many mobile games adopt autobattle systems in which the major consideration of players is
how to assemble strong teams. The automated team assembly (ATA) becomes a crucial …