abductive-hypothesis-generation

# Abductive Hypothesis Generation Inference to the best explanation in the face of anomalies: when an anomalous phenomenon that existing theory cannot explain is observed, systematically generate candidate explanations and select the most plausible one as the hypothesis. ## When to Use - A clear anomalous phenomenon is observed (a result inconsistent with existing theoretical predictions) - Existing theory cannot adequately explain a known phenomenon - One of several competing explanations must be selected as the most worth testing - The research starting point is "this result is strange, why?" Not applicable: no clear anomaly, just wanting to explore a new field → use inductive-hypothesis-generation instead. ## Thinking Framework **Anomaly → Generate candidate explanations → Rank by plausibility → Best explanation = hypothesis** The core logic of abductive reasoning: 1. **Anomaly**: precisely describe the anomaly — what phenomenon, inconsistent with what expectation, how large the deviation 2. **Generate candidate explanations**: systematically generate all candidate explanations that can account for the anomaly (no premature filtering) 3. **Rank by plausibility**: rank by plausibility — which explanation is most parsimonious, most consistent with known facts, most testable 4. **Best explanation = hypothesis**: select the most plausible explanation as the working hypothesis, retaining the rest as competing hypotheses **Core principles of abduction**: - **Occam's raz...