A Computationally Efficient Fuzzy Logic Parameterisation System for Computer Games

Linguistic fuzzy expert systems provide useful tools for the implementation of Artificial Intelligence (AI) systems for computer games. However, in games where a large number of fuzzy agents are needed, the computational needs of the fuzzy expert system inclines designers to abandon this promising technique in favour of non-fuzzy AI techniques with a lower computational overhead. In this paper we investigated a parameterisation of fuzzy sets with the goal of finding fuzzy systems that have lower computational needs but still have sufficient accuracy for use in the domain of computer games. We developed a system we call short-cut fuzzy logic that has low computational needs and seems to have adequate accuracy for the games domain.