| %% SKC-LISP: Layered Truth Maintenance System (LTMS) | |
| %% Knowledge layer: Prolog symbolic reasoning engine | |
| %% Author: Ahmad Parr (ahmedparr93@gmail.com) | |
| %% Integration: Snapkitty LISP Bridge knowledge engine | |
| :- dynamic fact/5. % fact(Value, Source, Timestamp, Confidence, Priority) | |
| :- dynamic rule/4. % rule(Head, Body, Module, Priority) | |
| :- dynamic concept/2. % concept(Name, Senses) | |
| :- dynamic sense/4. % sense(Concept, Gloss, ContextPred, Confidence) | |
| :- dynamic belief_base/1. % belief_base(Timestamp) for history | |
| :- dynamic module_stats/3. % module_stats(Module, RuleCount, LastUpdated) | |
| %% ============================================================================ | |
| %% 1. CONFLICT RESOLUTION | |
| %% ============================================================================ | |
| %% When multiple facts claim the same value, pick the winner by: | |
| %% Priority > Confidence > Source recency | |
| resolve_conflict(Value, Winner) :- | |
| findall(f(Value,S,T,C,P), fact(Value,S,T,C,P), Candidates), | |
| (Candidates = [] | |
| -> fail | |
| ; predsort(compare_facts, Candidates, Sorted), | |
| Sorted = [Winner|_]). | |
| %% Comparison: higher priority wins, then higher confidence | |
| compare_facts(Order, f(_,_,_,C1,P1), f(_,_,_,C2,P2)) :- | |
| ( P1 > P2 -> Order = (<) | |
| ; P1 < P2 -> Order = (>) | |
| ; C1 > C2 -> Order = (<) | |
| ; C1 < C2 -> Order = (>) | |
| ; Order = (=) ). | |
| %% Get the winning value | |
| get_belief(Value, WinningFact) :- | |
| resolve_conflict(Value, WinningFact). | |
| %% ============================================================================ | |
| %% 2. OUTDATED DETECTION | |
| %% ============================================================================ | |
| %% Exponential decay: confidence decays over time | |
| %% Decay function: Conf(t) = Conf(0) * exp(-0.0001 * age_in_ms) | |
| is_outdated(fact(_,_,Created,Conf,_), Now) :- | |
| Decay is Conf * exp(-0.0001 * (Now - Created)), | |
| Decay < 0.15. | |
| prune_outdated_facts(Now) :- | |
| findall(f(V,S,T,C,P), fact(V,S,T,C,P), AllFacts), | |
| forall(member(F, AllFacts), | |
| (is_outdated(F, Now) -> retract(F) ; true)). | |
| %% Half-life: time for confidence to drop to 50% | |
| compute_half_life(HalfLife) :- | |
| HalfLife is log(2.0) / 0.0001. % ~6931 milliseconds = 6.9 seconds | |
| %% ============================================================================ | |
| %% 3. AMBIGUOUS CONCEPTS | |
| %% ============================================================================ | |
| %% Concepts have multiple senses, each with a context predicate | |
| register_concept(Name, SenseGlosses) :- | |
| findall(sense(Name, Gloss, _, 1.0), member(Gloss, SenseGlosses), Senses), | |
| assertz(concept(Name, Senses)). | |
| disambiguate(Concept, Context, Sense) :- | |
| concept(Concept, Senses), | |
| member(sense(Concept, Gloss, Pred, Conf), Senses), | |
| (var(Pred) ; call(Pred, Context)), | |
| Sense = sense(Concept, Gloss, Pred, Conf). | |
| %% Pick best sense by confidence (or first if all equal) | |
| best_sense(Concept, Context, BestSense) :- | |
| findall(Sense, disambiguate(Concept, Context, Sense), Candidates), | |
| (Candidates = [] | |
| -> fail | |
| ; sort(Candidates, [BestSense|_])). | |
| %% ============================================================================ | |
| %% 4. MAINTAINABILITY GUARD | |
| %% ============================================================================ | |
| %% Hard limit: no module can have > 80 rules | |
| %% Prevents knowledge explosion and maintains readable rule sets | |
| assert_rule(Head, Body, Module, Priority) :- | |
| findall(_, rule(_,_,Module,_), Rules), | |
| length(Rules, N), | |
| (N >= 80 | |
| -> throw(error(module_overflow, | |
| context(assert_rule/4, | |
| "Module " + Module + " has reached rule limit"))) | |
| ; assertz(rule(Head, Body, Module, Priority)), | |
| update_module_stats(Module)). | |
| update_module_stats(Module) :- | |
| (retract(module_stats(Module, _, _)) ; true), | |
| findall(_, rule(_,_,Module,_), Rules), | |
| length(Rules, Count), | |
| get_time(Now), | |
| assertz(module_stats(Module, Count, Now)). | |
| %% Get module health (rules / max_rules) | |
| module_complexity(Module, Percentage) :- | |
| module_stats(Module, Count, _), | |
| Percentage is (Count / 80.0) * 100. | |
| %% Suggest refactoring when > 70% full | |
| suggest_refactor(Module) :- | |
| module_complexity(Module, P), | |
| P > 70.0. | |
| %% ============================================================================ | |
| %% 5. HYBRID / NON-RULE KNOWLEDGE | |
| %% ============================================================================ | |
| %% Fallback to embeddings when symbolic reasoning fails | |
| hybrid_prove(Goal, Result, Confidence) :- | |
| ( prove_symbolic(Goal, Result) | |
| -> Confidence = 1.0 | |
| ; embedding_retrieve(Goal, Result, Confidence) | |
| ). | |
| prove_symbolic(Goal, Result) :- | |
| clause(Goal, Body), | |
| call(Body), | |
| Result = Goal. | |
| %% Stub for embedding retrieval (connects to vector DB) | |
| embedding_retrieve(Goal, Result, Confidence) :- | |
| % In production: query Qdrant/WORM ledger for similar embeddings | |
| % For now: fail gracefully | |
| fail. | |
| %% ============================================================================ | |
| %% ASSERTION & QUERY API | |
| %% ============================================================================ | |
| %% Assert a new fact | |
| assert_fact(Value, Source, Confidence, Priority) :- | |
| get_time(Now), | |
| Timestamp is floor(Now * 1000), % milliseconds | |
| assertz(fact(Value, Source, Timestamp, Confidence, Priority)). | |
| %% Query belief about a value (returns winning fact + confidence) | |
| query(Value, Confidence) :- | |
| resolve_conflict(Value, f(Value, _, _, Confidence, _)). | |
| %% All known senses of a concept | |
| all_senses(Concept, AllSenses) :- | |
| concept(Concept, AllSenses). | |
| %% Concept subsumption: is Specific a kind of General? | |
| is_a(Specific, General) :- | |
| fact(is_a(Specific, General), _, _, _, _). | |
| %% ============================================================================ | |
| %% DEBUGGING & INSPECTION | |
| %% ============================================================================ | |
| %% List all facts | |
| list_facts :- | |
| findall(f(V,S,T,C,P), fact(V,S,T,C,P), Facts), | |
| forall(member(F, Facts), writeln(F)). | |
| %% List all rules by module | |
| list_rules_in_module(Module) :- | |
| findall(rule(H,B,M,Pr), rule(H,B,Module,Pr), Rules), | |
| forall(member(R, Rules), writeln(R)). | |
| %% List all concepts | |
| list_concepts :- | |
| findall(C, concept(C, _), Concepts), | |
| forall(member(C, Concepts), writeln(C)). | |
| %% Module report | |
| module_report :- | |
| findall(m(M,Count,Updated), module_stats(M,Count,Updated), Stats), | |
| forall(member(m(Mod,Count,_), Stats), | |
| format('~w: ~w/80 rules~n', [Mod, Count])). | |
| %% ============================================================================ | |
| %% TESTS | |
| %% ============================================================================ | |
| :- initialization(run_ltms_tests). | |
| run_ltms_tests :- | |
| writeln('=== LTMS Tests ==='), | |
| % Test 1: Conflict resolution | |
| writeln('Test 1: Conflict resolution'), | |
| assert_fact(color(car), source_a, 0.8, 10), | |
| assert_fact(color(car), source_b, 0.9, 5), | |
| resolve_conflict(color(car), Winner), | |
| writeln(Winner), nl, | |
| % Test 2: Outdated detection | |
| writeln('Test 2: Outdated detection'), | |
| get_time(Now), | |
| OldTime is (Now * 1000) - 10000, | |
| (is_outdated(fact(old_value, old_source, OldTime, 0.5, 1), Now * 1000) | |
| -> writeln('✓ Old fact marked as outdated') | |
| ; writeln('✗ Old fact not detected')), nl, | |
| % Test 3: Module limit | |
| writeln('Test 3: Module complexity guard'), | |
| (module_complexity(main, P), format('Main module: ~1f% full~n', [P]) | |
| ; writeln('Main module not yet used')), nl, | |
| writeln('=== LTMS Tests Complete ==='). | |