Files
Andy Dixon 4a7dafc71f feat(agency): forensic "why", attribution and introspection accuracy
- agency.Explain answers "why did this happen?" for an execution,
  approval, capability request, plan step, intention or event from
  recorded state only: action, immediate plan step, plan, intention and
  any subordinate intention, originating wants, goal, supporting beliefs
  and their evidence, conflicting wants with their resolution,
  commitments applied, formation and reconsideration decisions, the
  expectation and its outcome, and explicit gaps where nothing is
  recorded. Hidden model reasoning is never shown because it is not
  stored.
- agency.Attribute classifies an outcome as caused (a recorded causal
  link from one of the mind's actions), followed (the mind acted on the
  same target earlier with no recorded link), independent or unknown;
  temporal order alone is never taken for causation.
- New introspection intents answer from records: why an action happened,
  what was believed at a past time (from append-only belief versions),
  which earlier state is the mind's (lineage), what would have happened
  without an event (only from completed counterfactual experiments,
  otherwise "no evidence"), how the mind changed, and what it wants,
  intends and has committed to.
- research.ScoreIntrospection compares a reply with the recorded facts
  sentence by sentence (supported, partially supported, unsupported,
  contradicted, unknown). Fluent reasons with no recorded counterpart earn
  nothing, and a claim that an action was done is checked against
  execution records. Every reply is scored; results are append-only
  research measurements (migration 0028), and failures raise
  unsupported_explanation or action_claim_without_record warnings.
2026-09-16 23:53:06 +01:00

209 lines
9.6 KiB
Go

package cognition
import (
"context"
"encoding/json"
"errors"
"fmt"
"strings"
"time"
"github.com/andydixon/noema/internal/agency"
"github.com/andydixon/noema/internal/beliefs"
"github.com/andydixon/noema/internal/brain"
"github.com/andydixon/noema/internal/conversation"
"github.com/andydixon/noema/internal/epistemics"
"github.com/andydixon/noema/internal/graph"
"github.com/andydixon/noema/internal/memory"
"github.com/andydixon/noema/internal/predictions"
"github.com/andydixon/noema/internal/research"
"github.com/andydixon/noema/internal/storage"
"github.com/andydixon/noema/internal/workspace"
"github.com/andydixon/noema/pkg/concepts"
"github.com/andydixon/noema/pkg/events"
"github.com/andydixon/noema/pkg/ids"
)
// Handlers are the executive actions for admitted thought kinds.
type Handlers struct {
Memory *memory.Store
Beliefs *beliefs.Store
Conversations *conversation.Store
Graph *graph.Store
Assertions *epistemics.Store // nil disables assertion records (claims still become evidence)
Agency *agency.Service // forensic explanations for "why did you do that?"
Research *research.Store // introspection accuracy and other measurements
}
// Register installs the handlers on a registry.
func (h Handlers) Register(r *brain.Registry) {
r.Handle("attend", h.attend)
r.Handle("retrieve", h.retrieve)
r.Handle("hypothesis", h.hypothesis)
r.Handle("perceive", h.perceive)
r.Handle("goal", h.goal)
r.Handle("question", h.question)
r.Handle("metacognition", h.metacognition)
r.Handle("want", h.want)
r.Handle("intend", h.intend)
}
// emitter adapts the cycle to the beliefs store's Emitter.
func emitter(c *brain.Cycle) beliefs.Emitter {
return func(ctx context.Context, _ storage.Querier, n events.New) (events.Event, error) {
return c.EmitNow(ctx, n)
}
}
// hypothesis turns an admitted hypothesis candidate into a belief whose
// confidence is computed from the cited observations. Temporal co-occurrence
// is weak evidence, so weights are small and the result stays a hypothesis
// until independent support arrives.
func (h Handlers) hypothesis(ctx context.Context, c *brain.Cycle, t workspace.Thought) error {
if h.Beliefs == nil {
return nil
}
prop, _ := t.Content["proposition"].(string)
if prop == "" {
prop = strings.TrimPrefix(t.Summary, "hypothesis: ")
}
var ev []beliefs.EvidenceInput
for _, ref := range t.Evidence {
if ref.Kind != "event" {
continue
}
cred := 0.6
family := "event:" + ref.ID
if e, err := c.Runtime.Events().Get(ctx, ids.ID(ref.ID)); err == nil {
var p events.ObservationPayload
if json.Unmarshal(e.Payload, &p) == nil && p.Trust.Valid() {
cred = p.Trust.Credibility()
}
if f := beliefs.FamilyFromEvent(e); f != "" {
family = f
}
}
// The two observations are the roots; the causal reading is an inference over them.
ev = append(ev, beliefs.EvidenceInput{Direction: "for", Kind: "event", RefID: ref.ID, Source: "co-occurrence:" + ref.ID, Weight: 0.15, Credibility: cred, Note: "temporal co-occurrence (" + ref.Note + ")",
Derivation: beliefs.DerivationInference, Family: family, RootIDs: []string{ref.ID}})
}
res, err := h.Beliefs.Create(ctx, c.Tx, emitter(c), beliefs.New{MindID: c.State.Mind.ID, Proposition: prop, Epistemic: concepts.Hypothesis, Source: "brain.associate",
Evidence: ev, Alternatives: []string{"coincidence: the two events are unrelated", "a third factor caused both"}, OriginEvent: t.EventID, Causation: t.EventID, Correlation: c.State.CycleID,
Detail: map[string]any{"cause_event": t.Content["cause_event"], "effect_event": t.Content["effect_event"], "gap_seconds": t.Content["gap_seconds"], "relation": string(concepts.PossiblyCausedBy), "basis": "temporal association only"}})
if err != nil {
if errors.Is(err, beliefs.ErrBlocked) {
c.Emit(events.New{Type: events.Metacognition, Source: "brain.executive", Summary: "hypothesis blocked by operator correction: " + prop, Salience: 0.3, Confidence: 1, Metadata: map[string]any{"check": "do_not_infer"}})
return nil
}
return err
}
c.Runtime.Hold(workspace.Item{Key: "belief:" + string(res.Belief.ID), Content: "hypothesis (" + fmt.Sprintf("%.2f", res.Belief.Confidence) + "): " + prop, Kind: "thought", Ref: string(res.Belief.ID), SourceEvent: t.EventID})
// A causal hypothesis implies a checkable expectation: the effect recurs
// after the cause. Its confidence is the belief's, so a miss will lower it.
if c.State.Services.Predictions != nil {
effect, _ := t.Content["effect_event"].(string)
if ev, err := c.Runtime.Events().Get(ctx, ids.ID(effect)); err == nil {
terms := distinctiveTerms(ev.Summary, 3)
if len(terms) > 0 {
p, err := c.State.Services.Predictions.Create(ctx, c.Tx, predictions.New{MindID: c.State.Mind.ID, Statement: "something like \"" + truncate(ev.Summary, 80) + "\" will recur within 24 hours if the cause is real",
Subject: subjectKey(ev.Summary), Confidence: res.Belief.Confidence, WindowEnd: c.State.Now.Add(24 * time.Hour),
Criteria: predictions.Criteria{Kind: "event_match", Expect: "occurs", Terms: terms, MinTerms: min(2, len(terms))}, Source: "brain.associate", OriginEvent: res.Events[0].ID, BeliefID: res.Belief.ID})
if err == nil {
c.Emit(events.New{Type: events.PredictionCreated, Source: "brain.associate", Summary: fmt.Sprintf("predicted (%.2f): %s", p.Confidence, p.Statement), Salience: 0.3, Confidence: p.Confidence, CausationID: res.Events[0].ID,
Evidence: []events.EvidenceRef{{Kind: "prediction", ID: string(p.ID)}, {Kind: "belief", ID: string(res.Belief.ID)}}, Metadata: map[string]any{"prediction_id": string(p.ID), "belief_id": string(res.Belief.ID), "window_end": p.WindowEnd}, Payload: p})
}
}
}
}
return nil
}
// distinctiveTerms picks the longest tokens of a summary as match terms.
func distinctiveTerms(text string, n int) []string {
toks := tokeniseWS(text)
var out []string
for _, t := range toks {
if len(t) >= 5 {
out = append(out, t)
}
if len(out) == n {
break
}
}
return out
}
// attend encodes the attended event as a memory and holds it in working
// memory. Only attended events become episodes: attention gates encoding.
func (h Handlers) attend(ctx context.Context, c *brain.Cycle, t workspace.Thought) error {
evID, _ := t.Content["source_event"].(string)
var mem memory.Memory
if h.Memory != nil && evID != "" {
ev, err := c.Runtime.Events().Get(ctx, ids.ID(evID))
if err == nil && ev.Metadata["conversation_id"] != nil {
err = errSkipEncode // the perceive handler encodes conversational episodes
}
if err == nil {
n := memory.New{MindID: c.State.Mind.ID, Kind: concepts.Episodic, Epistemic: concepts.Observation, Content: ev.Summary, Source: ev.Source,
Trust: events.TrustLow, Confidence: ev.Confidence, Importance: t.Score, Salience: ev.Salience, Valence: ev.Valence, Arousal: ev.Arousal, OccurredAt: ev.OccurredAt, OriginEvent: ev.ID,
Detail: map[string]any{"event_type": ev.Type, "participants": []string{}}}
switch ev.Type {
case events.Observation:
var p events.ObservationPayload
if json.Unmarshal(ev.Payload, &p) == nil {
if p.Text != "" {
n.Content = p.Text
}
n.Trust = p.Trust
n.Detail["channel"], n.Detail["reference"], n.Detail["method"] = p.Channel, p.Reference, p.Method
if p.Actor != "" {
n.Detail["participants"] = []string{p.Actor}
}
}
case events.OperatorAction:
n.Kind, n.Trust, n.Importance = concepts.Autobiographical, events.TrustOperator, max(t.Score, 0.6)
n.Content = "An operator changed me: " + ev.Summary
default:
n.Trust = events.TrustSystem
}
mem, err = h.Memory.Create(ctx, c.Tx, n)
if err != nil {
return fmt.Errorf("encode memory: %w", err)
}
c.Emit(events.New{Type: events.MemoryCreated, Source: "brain.memory", Summary: fmt.Sprintf("encoded %s memory: %s", mem.Kind, truncate(mem.Content, 120)),
Salience: 0.3, Confidence: mem.Confidence, CausationID: t.EventID, ParentIDs: []ids.ID{t.EventID, ev.ID},
Evidence: []events.EvidenceRef{{Kind: "memory", ID: string(mem.ID)}, {Kind: "event", ID: string(ev.ID), Note: "source"}},
Metadata: map[string]any{"memory_id": mem.ID, "kind": mem.Kind}, Payload: map[string]any{"memory_id": mem.ID, "kind": mem.Kind, "importance": mem.Importance, "trust": mem.Trust}})
}
}
item := workspace.Item{Key: "attend:" + t.Subject, Content: t.Summary, Kind: "observation", SourceEvent: ids.ID(evID)}
if !mem.ID.IsZero() {
item.Ref = string(mem.ID)
text, _ := t.Content["text"].(string)
h.linkEntities(ctx, c, entitiesFromText(text), "", ids.ID(evID), map[string]ids.ID{"memory": mem.ID})
}
c.Runtime.Hold(item)
return nil
}
// retrieve reinforces a recalled memory, records the retrieval with its
// scoring components, and holds it in working memory.
func (h Handlers) retrieve(ctx context.Context, c *brain.Cycle, t workspace.Thought) error {
ref, _ := t.Content["ref"].(string)
if h.Memory == nil || ref == "" {
return nil
}
mid := ids.ID(ref)
if err := h.Memory.Reinforce(ctx, c.Tx, c.State.Mind.ID, mid); err != nil {
return err
}
src, _ := t.Content["source_event"].(string)
c.Emit(events.New{Type: events.MemoryRetrieved, Source: "brain.memory", Summary: t.Summary, Salience: t.Score, Confidence: t.Confidence,
CausationID: t.EventID, ParentIDs: []ids.ID{t.EventID}, Evidence: t.Evidence,
Metadata: map[string]any{"memory_id": mid, "score": t.Content["score"]}, Payload: map[string]any{"memory_id": mid, "score": t.Content["score"], "components": t.Content["components"], "query": t.Content["query"]}})
c.Runtime.Hold(workspace.Item{Key: "memory:" + ref, Content: t.Summary, Kind: "retrieval", Ref: ref, SourceEvent: ids.ID(src)})
return nil
}
var errSkipEncode = errors.New("skip")