Published on September 28, 2026, the collection presents 200 environments for studying reinforcement learning in challenging, open-ended, long-horizon tasks.
On September 28, 2026, FrontierSmith published 200 open problems for studying reinforcement learning (RL) on challenging tasks. Its description says a system uses AI to synthesize open-ended programming problems at scale; the problems provide environments for engineers to investigate open-ended, long-horizon tasks.
To check the scope and details, consult the project’s GitHub page and compare its description with the published problems. If you use AI to study or adapt the material, do not submit internal code, data, or documents unless your organization’s protection policy permits it.