{"results":[{"id":"beliefs-cli-vs-reasons-cli","text":"Two CLIs at different levels: beliefs CLI is a structured markdown KB with provenance and manual maintenance (simple, flat). reasons CLI (ftl-reasons) is a full TMS with automatic propagation, cascades, backtracking, and LLM-driven operations (powerful, dependency-aware). Use beliefs for independent facts, reasons for justified conclusions with dependency chains","truth_value":"IN","justification_count":0,"dependent_count":1,"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":"how-humans-use-eem","text":"Humans use EEM by: inspecting beliefs.md for current state, running reasons explain to understand why something is believed, challenging beliefs with reasons challenge, reviewing the network with reasons status, checking staleness with reasons check-stale. The key value is visibility — humans can see and audit what the system knows","truth_value":"IN","justification_count":1,"dependent_count":0,"challenges":[],"last_reviewed":null,"review_result":null},{"id":"how-to-start","text":"To start using EEM: (1) reasons init — creates reasons.db, (2) add premises from observations with reasons add, (3) add justified conclusions with --sl to link dependencies, (4) use reasons derive to find connections, (5) use reasons review-beliefs to audit, (6) retract when evidence changes and let cascades propagate","truth_value":"IN","justification_count":1,"dependent_count":0,"challenges":[],"last_reviewed":null,"review_result":null},{"id":"hybrid-tms","text":"ftl-reasons is a hybrid TMS: symbolic TMS handles structure (justifications, propagation, cascades, backtracking, challenge/defend) while LLMs handle semantic operations (derive generates beliefs, review-beliefs critiques them, contradiction detection finds nogoods)","truth_value":"IN","justification_count":1,"dependent_count":4,"challenges":[],"last_reviewed":null,"review_result":null},{"id":"reasons-for-maintenance-beliefs-for-queries","text":"Architecture pattern: use reasons database for all structural operations (add, retract, derive, review). Export to beliefs.md for querying (fast, human-readable, grep-able). Keep both in sync via reasons export-markdown","truth_value":"IN","justification_count":1,"dependent_count":0,"challenges":[],"last_reviewed":null,"review_result":null}],"count":6,"limit":20,"offset":0}