Chapter 47. Learning Reactive Strategies
This chapter uses adaptation to find the most suitable deathmatch strategies. A variety of reinforcement learning (RL) algorithms are used as tools to craft behaviors automatically. This still requires involvement from the AI engineer, but the role involves designing software instead of implementing it. From a designer's point of view, this new system is easier to adjust implicitly but somewhat harder to control explicitly. From the point of view of gameplay, the RL approach allows adaptation, which provides interesting challenges for the players.
The next few pages cover the creation of an AI architecture to learn high-level behaviors, according to evaluative feedback (that is, the moods).
This chapter covers the following topics:
This chapter creates a fully working reactive animat, using reinforcement signals to adapt its behavior.