Congestion games are a well-studied class of games that has been used to model real-world systems such as Internet routing. In many congestion games, each player’s number of strategies can be exponential in the natural description of the game. Most existing algorithms for game theoretic computation, from computing expected utilities and best responses to finding Nash equilibrium and other solut...

Today, Real-Time Strategy (RTS) games entertain tens of millions of players world-wide. This growing population expects new game designs and more scalable games every year. However, few tools and environments exist for game designers and implementers; of these, even fewer are available to researchers and game communities. In this work, we introduce RTSenv, an environment and associated set of t...

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 ...

This paper advocates the exploration of the full state of recorded real-time strategy (RTS) games, by human or robotic players, to discover how to reason about tactics and strategy. We present a dataset of StarCraft games encompassing the most of the games’ state (not only player’s orders). We explain one of the possible usages of this dataset by clustering armies on their compositions. This re...

Pathfinding is a core component of many games especially real-time strategy games. The paper proposed a smooth path generation strategy based on the A * algorithm. Firstly, adopted an admissible heuristics function, and a key-point optimization is applied to make the path to be connected by a series of key points. Secondly, the paper applied Catmull-Rom splines to the key points interpolation, ...

Real Time Strategy (RTS) games provide complex domain to test the latest artificial intelligence (AI) research. In much of the literature, AI systems have been limited to playing one game. Although, this specialization has resulted in stronger AI gaming systems it does not address the key concerns of AI researcher. AI researchers seek the development of AI agents that can autonomously interpret...

In recent years, several real-time or near real-time object detectors have been developed. However these object detectors are typically designed for first-person view images where the subject is large in the image and do not directly apply well to detecting vehicles in aerial imagery. Though some detectors have been developed for aerial imagery, these are either slow or do not handle multi-scal...

This paper describes a goal-based architecture which provides a single source for all high level decisions made by AI players in real-time strategy games. The architecture is easily extensible, flexible enough to be rapidly adapted to multiple different games, and powerful enough to provide a good challenge on a random, unexplored map without unfair advantages or visible cheating. This framewor...

In Real-Time Strategy (RTS) games, players develop an army in real time, then attempt to take out one or more opponents. Despite the existence of basic similarities among the many di erent RTS games, engines of these games are often built ad hoc, and code re-use among di erent titles is minimal. We created a design pattern called Resource Entity Action (REA) that abstracts the basic interaction...