RL-Framework 0.9 beta
The RL-Framework is intended to provide a foundation for building benchmarks for reinforcement learning (RL) agents.
A secondary goal is to support RL competitions in which agents are compared in their performance on new problems that are only revealed at the time of a competition.
The current version of the interface software supports direct function call communication between agents and environments written in C.
The interface software also provides a standard mechanism for communication between agents and environments written in different programming languages.
tags and environments environments written agents and between agents interface software communication between the interface
Download RL-Framework 0.9 beta
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