태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
The StarCraft Multi-Agent Challenge (SMAC) is a benchmark that provides elements of partial observability, challenging dynamics, and high-dimensional observation spaces. SMAC is built using the StarCraft II game engine, creating a testbed for research in cooperative MARL where each game unit is an independent RL agent.
출처에 같은 태스크 이름으로 연결된 데이터셋입니다. 동명 태스크가 포함될 수 있으므로, 비교할 때는 평가 결과의 조건도 확인하세요.
The StarCraft Multi-Agent Challenge (SMAC) is a benchmark that provides elements of partial observability, challenging dynamics, and high-dimensional observation spaces. SMAC is built using the StarCraft II game engine, creating a testbed for research in cooperative MARL where each game unit is an independent RL agent.
The StarCraft Multi-Agent Challenges+ requires agents to learn completion of multi-stage tasks and usage of environmental factors without precise reward functions. The previous challenges (SMAC) recognized as a standard benchmark of Multi-Agent Reinforcement Learning are mainly concerned with ensuring that all agents cooperatively eliminate approaching adversaries only through fine manipulation with obvious reward functions. This challenge, on the other hand, is interested in the exploration capability of MARL algorithms to efficiently learn implicit multi-stage tasks and environmental factors as well as micro-control. This study covers both offensive and defensive scenarios. In the offensive scenarios, agents must learn to first find opponents and then eliminate them. The defensive scenarios require agents to use topographic features. For example, agents need to position themselves behind protective structures to make it harder for enemies to attack.
SMAC+ defensive armored scenario with sequential episodic buffer
smac+ defense infantry scenario with parallel episodic buffer
SMAC+ defensive infantry scenario with sequential episodic buffer
SMAC+ defensive outnumbered scenario with sequential episodic buffer
smac+ defense armored scenario with parallel episodic buffer
smac+ defense outnumbered scenario with parallel episodic buffer
smac+ offensive hard scenario with 20 parallel episodic buffer.
smac+ offensive scenario with 20 parallel episodic buffer.
smac+ offensive complicated scenario with 20 parallel episodic buffer.
SMAC+ offense distant scenario.
smac+ offensive near scenario with 20 parallel episodic buffer
SMAC+ offensive complicated scenario with sequential episodic buffer
SMAC+ offensive distant scenario with sequential episodic buffer
SMAC+ offensive hard scenario with sequential episodic buffer
SMAC+ offensive near scenario with sequential episodic buffer
SMAC+ offensive superhard scenario with sequential episodic buffer
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.