Papers with Code · CC BY-SA 4.0

SMAC+

SMAC › SMAC+ 133 평가 기록 16 datasets

Bechmarks for Efficient Exploration of Completion of Multi-stage Tasks and Usage of Environmental Factors

논문

DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning

2102.07936 2021-02-16 이 페이지의 평가 6건

Median Win Rate: 0.0

Disentangling Sources of Risk for Distributional Multi-Agent Reinforcement Learning

2021-09-29 이 페이지의 평가 5건

Median Win Rate: 15.6

Counterfactual Multi-Agent Policy Gradients

1705.08926 2017-05-24 이 페이지의 평가 4건

Median Win Rate: 0.0

QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning

1803.11485 2018-03-30 이 페이지의 평가 4건

Median Win Rate: 0.0

Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments

1706.02275 2017-06-07 이 페이지의 평가 3건

Median Win Rate: 0.0

Decomposed Soft Actor-Critic Method for Cooperative Multi-Agent Reinforcement Learning

2104.06655 2021-04-14 이 페이지의 평가 2건

Median Win Rate: 0.0

QTRAN: Learning to Factorize with Transformation for Cooperative Multi-Agent Reinforcement Learning

1905.05408 2019-05-14 이 페이지의 평가 2건

Median Win Rate: 0.0

The StarCraft Multi-Agent Challenges+ : Learning of Multi-Stage Tasks and Environmental Factors without Precise Reward Functions

2207.02007 2022-07-05 이 페이지의 평가 2건

Median Win Rate: 0.0

Value-Decomposition Networks For Cooperative Multi-Agent Learning

1706.05296 2017-06-16 이 페이지의 평가 2건

Median Win Rate: 15.0