This is the Linux app named Scalable Distributed Deep-RL whose latest release can be downloaded as scalable_agentsourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
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Deep-RL distribué et évolutif
DESCRIPTION
Scalable Agent is the open implementation of IMPALA (Importance Weighted Actor-Learner Architectures), a highly scalable distributed reinforcement learning framework developed by Google DeepMind. IMPALA introduced a new paradigm for efficiently training agents across large-scale environments by decoupling acting and learning processes. In this architecture, multiple actor processes interact with their environments in parallel to collect trajectories, which are then asynchronously sent to a centralized learner for policy updates. The learner uses importance weighting to correct for policy lag between actors and the learner, enabling stable off-policy training at scale. This design allows the system to scale efficiently to hundreds of environments and billions of frames while maintaining sample efficiency and stability. The implementation supports training in DeepMind Lab (DMLab) and has also been adapted for other environments like Atari and Street View.
Comment ça marche
- Implements IMPALA, a scalable distributed deep reinforcement learning framework
- Supports asynchronous actor-learner architecture with importance weighting
- Efficiently trains agents on large-scale environments (e.g., DMLab-30, Atari)
- Includes dynamic batching for optimized data throughput
- Compatible with DeepMind Sonnet and TensorFlow
- Provides Dockerfile setup for reproducible single-machine or distributed training
Langage de programmation
C++, Python
Catégories
This is an application that can also be fetched from https://sourceforge.net/projects/scalable-dist-deep-rl.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.
