Type-2 Fuzzy Logic-Based Linguistic Pursuing Strategy Design and Its Deployment to a Real-World Pursuit Evasion Game

Abstract

This paper presents a systematic and interpretable design approach to generate type-2 (T2) fuzzy logic-based linguistic pursuing strategies (PSs) and their deployment to a real-world pursuit-evasion game (PEG). First, we have developed a novel T2 fuzzy logic-based strategy planner (T2-FSP). Then, through detailed theoretical investigations on the input-output mapping of the T2-FSP, it has been shown that it is possible to design a linguistic PS which defines both pursuer's approaching behavior (aggressive, smooth) and side (left or right) to the evader by simply tuning the footprint of uncertainty (FOU) sizes of the T2 fuzzy sets. Hence, an interpretable relationship has been revealed between the FOU sizes and the PSs through comparative theoretical explorations and derivations. Additionally, as there is a need to employ different PSs in a dynamic PEG environment, a type-1 fuzzy decision making (T1-FDM) mechanism has been designed to tune the FOU sizes of the T2-FSP and, thus, adjust the PS to be employed in real time. A real-world game environment is constructed in order to validate the developed T2 fuzzy logic-based PSs and T1-FDM mechanism in real time. Comparative experimental results have been presented to show that the T2 fuzzy logic-based PSs have satisfactory performance against a human user.