Andy Dixon
9eb873cbe6
Phase 9. Goals form a mind-scoped tree with kind, priority, progress and blockers; their deterministic relevance to a candidate feeds the goal_relevance attention feature and a goal monitor raises stalled goals and observations that touch one. Drives are a closed set of eight scalars with operator-configured ranges and personality-derived baselines; there is no self-preservation, replication or acquisition drive and no way to add one at runtime. Affect is ten scalars moved by an explicit rule table over events and decaying towards baseline; both modulate attention weights each cycle and the effective weights are recorded with every cycle and shown beside the configured ones. Predictions carry a window and machine-checkable criteria (event terms occurring or staying absent, a belief reaching a confidence, or operator judgement). A resolver job judges them deterministically, keeps an append-only outcome history for calibration (accuracy, Brier score, confidence buckets, overconfidence flag), emits prediction_error events scaled by how confident the miss was, and feeds the outcome back into the linked belief as evidence. Causal hypotheses derive predictions automatically. Curiosity turns misses, contradictions and unexplained observations into questions that compete for attention and become investigation goals when admitted. Brain gains after-cycle hooks and goal/motivation state. API, UI (goals, prediction dashboard, cognitive state panel, effective weights) and CLI (goal, prediction, state). Demo scenario 4 verified end to end.
2.7 KiB
2.7 KiB
Changelog
All notable changes to Noema are recorded here. Format follows Keep a Changelog; versions follow SemVer.
[Unreleased]
Added
- Phase 9 motivation: goal tree with attention relevance, closed drive set and rule-driven affect state with decay and weight modulation, explicit predictions with deterministic resolution, prediction errors feeding beliefs, calibration dashboard, curiosity questions becoming investigation goals.
- Phase 8 conversation (milestone M1): messages become observations, deterministic perception with optional model enrichment, claims become evidenced beliefs, grounded introspective answers from real state, model or deterministic wording with full provenance, chat UI,
noemactl ask, sample mind Dani with a strict seed import, and an end-to-end acceptance test. - Phase 7 LLM layer: provider-neutral router with roles and fallbacks, OpenAI-compatible/Anthropic/Ollama providers, encrypted secret references, SSRF-safe HTTP client, budgets, full call recording with replay, versioned prompts with untrusted data blocks, configuration and prompt manager UI, CLI.
- Phase 6 beliefs: evidence-derived confidence with inspectable arithmetic, statuses, alternatives, append-only history, deterministic contradiction detection, temporal-association hypotheses, operator corrections (wrong, do-not-infer, inaccurate memory), belief explorer and CLI.
- Phase 5 memory: episodic/semantic/procedural/autobiographical memory with epistemic status, fused retrieval with inspectable component scores, optional pgvector embeddings, decay without deletion, attention-gated encoding, retrieval process, memory explorer and CLI.
- Phase 4 cognition core: deterministic attention scoring with inspectable breakdowns, global workspace and working memory with decay, per-mind cognitive runtime with bounded concurrent processes, loop detection, operator controls, live workspace page and CLI.
- Phase 3 events: append-only cognitive event store with provenance links, filtered queries, durable cursors, live SSE streams with resume, forensic event explorer UI, thought stream page, operator observations and CLI.
- Phase 2 minds: structured personalities with append-only version history, diff, restore, templates with preserved overrides, self-model, mind lifecycle (create, clone, disable, archive), API, UI editor and CLI.
- Phase 1 foundation: configuration, structured logging, metrics, migrations, local authentication (Argon2id, sessions, CSRF, lockout, roles, API tokens), audit log, JSON API skeleton, server-rendered admin UI with light/dark theme,
noemadandnoemactl. - Repository foundation: plan, architecture, security model, threat model, ADRs, Makefile, container files.