reinforcement-learningdeep-reinforcement-learningpytorchmulti-agentdqnrldeep-q-networkddpgdrlactor-criticdeep-deterministic-policy-gradientproximal-policy-optimizationppoadvantage-actor-critica2cacktrmadrl UpdatedNov 11, 2017 Python 🐝 GPTSwarm: LLM agents as (Optimizable) Graphs ...
reinforcement-learningdecision-makingpytorchdqnatariddpgmpemujocoppomagentstarcraft2a2cmulti-agent-reinforcement-learningmaddpgtensorflow2google-research-footballmindsporeqmixmapporeinforcement-learning-library UpdatedOct 3, 2024 Python AgileRL/AgileRL Sponsor ...
In this work, we introduce the Vectorized Multi-Agent Simulator (VMAS). VMAS is an open-source framework designed for efficient MARL benchmarking. It is comprised of a vectorized 2D physics engine written in PyTorch and a set of twelve challenging multi-robot scenarios. Additional scenarios can...
Multi-agent pathfinding (MAPF) is a critical field in many large-scale robotic applications, often being the fundamental step in multi-agent systems. The increasing complexity of MAPF in complex and crowded environments, however, critically diminishes the effectiveness of existing solutions. In contrast...
PPO agent * Fix torch deprecated warning * Reduce and broadcast learning rate across all workers/processes * Update CHANGELOG * Implement distributed runs for on-policy agents * Add distributed implementation to agent features * Implement distributed runs for off-policy agents * Update off-policy ...
a multi-agent variant of PPO. The implementation in this repositorory is used in the paper "The Surprising Effectiveness of PPO in Cooperative Multi-Agent Games" (https://arxiv.org/abs/2103.01955). This repository is heavily based onhttps://github.com/ikostrikov/pytorch-a2c-ppo-acktr-gail....
Diepold. Multi-agent deep reinforcement learning: A survey. Artificial Intelligence Review, vol. 55, no. 2, pp. 895–943, 2022. DOI: https://doi.org/10.1007/s10462-021-09996-w. Article Google Scholar Y. D. Yang, J. Wang. An overview of multi-agent reinforcement learning from game ...
a multi-agent variant of PPO. The implementation in this repositorory is used in the paper "The Surprising Effectiveness of PPO in Cooperative Multi-Agent Games" (https://arxiv.org/abs/2103.01955). This repository is heavily based onhttps://github.com/ikostrikov/pytorch-a2c-ppo-acktr-gail....
I am using a multi-agent setup with PPO and PyTorch. I set up a basic environment and now want to run serving in this environment. This works fine with TensorFlow, but when using PyTorch the exception can't convert CUDA tensor to numpy. Use Tensor.cpu() to copy the tensor to host me...
As a variant of proximal policy optimization (PPO) specialized for multi-agent settings, Multi-Agent Proximal Policy Optimization (MAPPO) is one of the state-of-the-art MARL algorithms [35]. The algorithm adopts centralized training with decentralized execution (CTDE) architecture and has high ...