A Dyna-Q (Lambda) Approach to Flocking with Fixed-Wing UAVs in a Stochastic Environment
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Bibliographic record
Abstract
Unmanned Aerial Vehicles (UAVs) have demonstrated their efficacy in supporting both military and civilian applications, many of which contain tasks that are parallel in nature, and can benefit from cooperation in terms of effectiveness. One of the fundamental challenges of multi-UAV systems is autonomous team coordination. This paper looks at flocking with small fixed-wing UAVs in the context of a model-free reinforcement learning problem. Dyna-Q ( ) with a variable learning rate is employed by the agents to learn a control policy that facilitates flocking in a leader-follower topology while operating in a stochastic environment. Simulation results demonstrate the followers learning and adapting their policies to non-stationary stochastic environments.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it