rlmulti-agentadvanced
Multi-agent reinforcement learning
MARL: independent learners, centralised training, QMIX, MAPPO — cooperation and competition among RL agents.
Уровни глубины
L0Intro~2ч
Knows "multiple agents, same environment" differs from single-agent RL.
L1Basics~10ч
Trains independent Q-learners on Pong 2-player; understands non-stationarity.
L2Working~20ч
Implements centralised-training / decentralised-execution (MADDPG, QMIX, MAPPO).
L3Advanced~30ч
Stochastic games; Nash / correlated equilibria; population-based training.
L4Research~60ч
Opponent modelling, emergent communication, large-scale MARL benchmarks (SMACv2).