{"results":[{"id":"atms-de-kleer-1986","text":"de Kleer (1986) ATMS uses assumption-based environments and nogoods. TMS beats ATMS for EEM because revision matters more than multiple environments when the problem solver (LLM) produces 13-37% errors","truth_value":"IN","justification_count":0,"dependent_count":0,"challenges":[],"last_reviewed":null,"review_result":null},{"id":"continuity-human-problem","text":"The human cannot track what the LLM currently has in context. EEM solves this via visibility and persistence — the human can always inspect the current belief state. Short compaction cycles are better than large context windows","truth_value":"IN","justification_count":1,"dependent_count":1,"challenges":[],"last_reviewed":null,"review_result":null},{"id":"frame-problem","text":"McCarthy & Hayes (1969) frame problem: what persists across state changes. check-stale addresses this by detecting when source files change under beliefs","truth_value":"IN","justification_count":0,"dependent_count":0,"challenges":[],"last_reviewed":null,"review_result":null},{"id":"ftl-reasons-is-tms","text":"ftl-reasons implements actual Doyle-style TMS architecture: SL justifications with antecedents and outlists, BFS propagation cascades with restoration, entrenchment-scored dependency-directed backtracking. LLMs fill the problem-solver role Doyle left open","truth_value":"IN","justification_count":1,"dependent_count":6,"challenges":[],"last_reviewed":null,"review_result":null},{"id":"llm-as-problem-solver","text":"Putting an LLM in the TMS problem-solver slot (generator via derive, critic via review-beliefs and contradiction detection) is what Doyle's architecture prescribes. The open question is whether an LLM is a good problem solver, not whether using one is faithful to the design","truth_value":"IN","justification_count":1,"dependent_count":1,"challenges":[],"last_reviewed":null,"review_result":null},{"id":"self-improvement","text":"The system finds problems in itself. Each improvement improves the system's ability to find the next improvement — exponential compounding vs linear improvement in static systems","truth_value":"IN","justification_count":1,"dependent_count":0,"challenges":[],"last_reviewed":null,"review_result":null},{"id":"tms-doyle-1979","text":"Doyle (1979) designed Truth Maintenance Systems with SL justifications, propagation, retraction cascades, and an exogenous problem-solver slot. The TMS substrate is content-agnostic by design","truth_value":"IN","justification_count":0,"dependent_count":2,"challenges":[],"last_reviewed":null,"review_result":null}],"count":7,"limit":20,"offset":0}