This is the Linux app named TRFL whose latest release can be downloaded as trflsourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
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TRFL
DESCRIPTION
TRFL, developed by Google DeepMind, is a TensorFlow-based library that provides a collection of essential building blocks for reinforcement learning (RL) algorithms. Pronounced “truffle,” it simplifies the implementation of RL agents by offering reusable components such as loss functions, value estimation tools, and temporal difference (TD) learning operators. The library is designed to integrate seamlessly with TensorFlow, allowing users to define differentiable RL objectives and train models using standard optimization routines. TRFL supports both CPU and GPU TensorFlow environments, though TensorFlow itself must be installed separately. It exposes clean, modular APIs for various RL methods including Q-learning, policy gradient, and actor-critic algorithms, among others. Each function returns not only the computed loss tensor but also a detailed structure containing auxiliary information like TD errors and targets.
Features
- Provides modular TensorFlow operations for reinforcement learning algorithms
- Includes Q-learning, actor-critic, policy gradient, and value-based losses
- Returns structured outputs with loss and diagnostic information
- Fully differentiable for use in end-to-end RL training pipelines
- Works with both CPU and GPU versions of TensorFlow
- Lightweight design for easy integration into custom RL research projects
Programming Language
Python
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/trfl.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.
