A Game Between a Terrorist and a Passive Defender
Bibliographic record
Abstract
In the last two decades, terrorism has become a major issue around the world. We analyze a continuous conflict between a terrorist (Terrorist) and a passive defender (Defender). Defender is passive because her actions can influence only the costs (damages) when Terrorist attacks. We focus on high‐trajectory fire attacks and passive responses to them in the conflict between Israel and the various terrorist groups in the Gaza Strip in accordance with scientific principles. We first consider three sources of data on this part of the conflict and based on these data we make several observations on the sustainability of cease fires, the use of technologies, different attacks, and the frequency of attacks, using high‐trajectory fire. To explain these observations, we present several stylized game theoretical models. Specifically, we consider single‐ and multi‐period games. In each period, Terrorist may attack Defender, who may in turn try to prevent damage. We show that given this conflict's political situation, our models are in agreement with the observations from the data. We also present an extension that considers an active defender. This extension also agrees with the observations from the data.
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How this classification was reachedexpand
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 | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".