Much research in artificial intelligence is concerned with the development of autonomous
agents that can interact effectively with other agents. An important aspect of such agents is …

This paper investigates strategies to generate levels for action-adventure games. For this
genre, level design is more critical than for rule-driven genres such as simulation or rogue …

In previous work we introduced a novel approach to adaptive game AI that was focussed on
the rapid and reliable adaptation to game circumstances. We named the approach 'case …

Current approaches to organising units in strategic video games are typically implemented
via static formations. Static formations are not capable of adapting effectively to opponent …

This paper proposes a similarity-based approach for opponent modelling in multi-agent
games. The classification accuracy is increased by adding derived attributes from imperfect …

Homeland security requires technologies capable of positive and reliable identification of
humans for law enforcement, government, and commercial applications. As artificially …

This paper investigates strategies to generate levels for action-adventure games. This genre
relies more strongly on well-designed levels than rule-driven genres such as strategy or role …

This paper proposes an algorithm to better solve the exploration-exploitation dilemma faced
by model-less reinforcement learning agents. The main contribution is twofold:(1) The two …

In the early s, the video-game industry has grown to surpass the Hollywood movie
industry in revenues. In recent years, video gaming has become a mass-market …

We present a first application of a general approach to learn the behavior of NPCs (and
other entities) in a game from observing just the graphical output of the game during game …