We attack the problem of controlling teams of autonomous units during skirmishes in real-time strategy games. Earlier work had shown promise in evolving control algorithm parameters that lead to high performance team behaviors similar to those favored by good human players in real-time strategy games like Starcraft. This algorithm specifically encoded parameterized kiting and fleeing behaviors ...

Analysis of behavioral data represents today a big issue, as so many domains generate huge quantity of activity and mobility traces. When traces are labeled by the user that generates it, models can be learned to accurately predict the user of an unknown trace. In online systems however, users may have several virtual identities, or duplicate labels. By ignoring them, the prediction accuracy dr...

Starcraft, a commercial Real-Time Strategy (RTS) game that has enjoyed world-wide popularity (including televised professional matches), is a challenging domain for automated computer agents. Evidence of this difficulty comes not only from characteristics of the game (massive state space, stochastic actions, partial visibility, etc.) but also from three years of competitive entries in tournamen...

Digital zero-sum games are a challenging domain for artificial intelligence techniques. In such games, human players often resort to strategies, i.e., memorized sequences of lowlevel actions that guide their behavior. In this research we model this way of playing by introducing the algorithm selection metagame, in which agents select algorithms to perform low-level game actions on their behalf....

This document summarises my research in the area of RealTime Strategy (RTS) video game Artificial Intelligence (AI). The main objective of this research is to increase the quality of AI used in commercial RTS games, which has seen little improvement over the past decade. This objective will be addressed by investigating the use of a learning by observation, case-based reasoning agent, which can...

Competitive and professional gaming, in which video game players participate in tournaments, offers numerous opportunities for much-needed research and enhanced knowledge about digital technology. To date, competitive gaming has received scant scientific attention, even though it may foster the development of adaptive skills or, in other instances, carry adverse consequences. Examining the life...

Professional competitive gaming has grown increasingly lucrative over the past 2 years since the release of Blizzard Entertainment’s real-time strategy game, StarCraft II: Wings of Liberty (SC2). Since there is no widely used SC2 map generator, most maps are hand-crafted by level designers who may not be in touch with the game’s intricate and shifting strategy, resulting in inconsistent game qu...

We present a drive-based agent capable of playing the realtime strategy computer game Starcraft. Success at this task requires the ability to engage in autonomous, goal-directed behaviour, as well as techniques to manage the problem of potential goal conflicts. To address this, we show how a caseinjected genetic algorithm can be used to learn goal priority profiles for use in goal management. T...

For now over a decade, real-time strategy (RTS) games have been challenging intelligence, human and artificial (AI) alike, as one of the top genre in terms of overall complexity. RTS is a prime example problem featuring multiple interacting imperfect decision makers. Elaborate dynamics, partial observability, as well as a rapidly diverging action space render rational decision making somehow el...