ABSTRACT
Smart decision-making at the tactical level is important for AI agents to perform well in real-time strategy (RTS) games, in which winning battles is crucial. This chapter describes an outcome evaluation model based on Lanchester's attrition laws, which were introduced in Lanchester's seminal book Aircraft in Warfare: The Dawn of the Fourth Arm in 1916. Scripted behavior is a common choice for making some decisions, due to the ease of implementation and very fast execution. Scripts can be tailored to any game or situation. Technically, simulations do not directly predict the winner but provide information about potential states of the world after a set of actions. The original Lanchester equations represent simplified combat models: each side has identical soldiers and a fixed strength, which governs the proportion of enemy soldiers killed. In RTS games, it is often the case that both armies are composed of various units, with different capabilities.
