Q-Learning Swarm Foraging 2026: Multi-Agent RL in Dynamic Grid Environments

A simulation of unsupervised (STDP) and reinforcement learning (Reward-based STDP) in human brain

Program an agent to learn the optimal route through a maze using reward-based action selection

Multi-Agent Reinforcement Learning project implementing Q-Learning for autonomous forager agents in a dynamic grid environment with renewable resources and obstacle navigation.