Reinforcement Learning–Inspired Adjustment Module

This module provides a production-ready implementation of a portfolio weight adjustment mechanism inspired by reinforcement learning. It updates weights using a simple multiplicative rule based on a reward signal, ensuring the portfolio remains valid and normalized.