Fuzzy Logic for Reinforcement Learning

[amogorkon]

Feature: Add support for integrating fuzzy logic with reinforcement learning (RL) algorithms.

Benefit: Fuzzy logic can help handle uncertainty in RL environments, improve exploration strategies, or interpret policy decisions.

Example: A fuzzy logic-based reward function that provides more nuanced feedback to an RL agent based on imprecise goals.