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Fuzzy Logic for Reinforcement Learning #78

@amogorkon

Description

@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.

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