Machine Learning Approach for Multiple Coordinated Aerial Drones Pursuit-Evasion Games
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Bibliographic record
Abstract
This paper presents a machine-learning algorithm applied to a quadcopter application. We are proposing a fuzzy actor-critic learning (FACL) algorithm. This method enables a pursuer quadcopter to capture an evader quadcopter in the pursuit-evasion (PE) differential game. In this application, the pursuer learns its control strategies by interacting with evader and learning from past experiences. Both the critique and the actor are fuzzy inference systems (FIS). It is assumed that the pursuer knows only the instantaneous position and speed of the evader and vice versa. The FACL will generate the desired trajectory as the input for low-level controllers. Simulation results are presented for the PE differential game to demonstrate the practicality of our machine-learning algorithm.
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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 | 0.000 | 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