Predator-Prey
Emerging6papers using it
2024first seen
The 'Predator-Prey' dataset is a discrete-action multi-agent reinforcement learning task used to evaluate the performance of algorithms like MADDPG in terms of learning stability and inter-agent cooperation.
Papers using Predator-Prey (6)
- Enhancing the MADDPG Algorithm for Multi-Agent Learning via Action Inference and Importance SamplingNucleolus Credit Assignment for Effective Coalitions in Multi-agent
Reinforcement LearningFinding the Weakest Link: Adversarial Attack against Multi-Agent CommunicationsWireless Communication Enhanced Value Decomposition for Multi-Agent Reinforcement LearningFluid-Agent Reinforcement LearningRobust Coordination under Misaligned Communication via Power
Regularization