Learning to autonomy
Autonomous control
Question
Research question
How can learned policies make useful decisions in physical systems while remaining measurable, bounded, and understandable?
Related work
Connected systems
Experiment
Deep RL Lunar Lander
First completed Deep RL environment with a recorded policy replay.
Evidence
Recorded outputs
EnvironmentLunarLander
MethodDeep RL
ReplayRecorded
BenchmarkNot recorded
The replay is qualitative evidence of learned behavior; reward and robustness benchmarks are not inferred.
Conclusion
Current conclusion
The progression now includes neural RL, but learned behavior in a benchmark environment is not yet evidence of robust autonomous flight.
Next question
What I would test next
Which evaluation protocol should expose policy stability, constraint violations, and generalization before higher-fidelity control tests?