Hyperon AI Algorithms+NACE (Non-Axiomatic Causal Explorer)+NACE Full

Source Verdict

Per Non-clustered HAA cluster pilot Source 5 close 2026-05-07: [IMPLEMENTATION-BACKED-CORE] / [AIRIS-DERIVED-NAL-ADJACENT] / [NACE-NOT-AIRIS] / [PARTIALLY-INTEGRATED-VIA-METTA-BRIDGE].

NACE is a real implementation, not a paper sketch. Pure-Python at HEAD 361fddf (2025-05-06; git ls-tree -r HEAD --name-only shows 13 .py files + 4 .metta files; no src/ directory, no *.cpp files; Qt-support per the recent commit message is via PyQt bindings in gui.py, not C++ Qt). The repo extends Berick Cook's AIRIS apparatus with partial observability, nondeterminism, nonstationarity, external changes, and Non-Axiomatic Logic (NAL) frequency/confidence evidence tracking. Distinct from AIRIS (closed HAA Source 1 2026-05-06) and from MeTTa-NARS (closed HAA Source 5 2026-05-07).

Core Mechanisms (file-line evidence)

The implementation is centered in nace.py:

• Causal-rule learning. Cognitive schematics in the form (precondition, operation) => consequence, learned through direct interaction with the environment. README.md:5-9.
• AIRIS confidence inheritance. nace.py:49 returns airis_score from _Plan; nace.py:189 annotates the score as "AIRIS confidence"; nace.py:198 describes planning that searches for highest reward, "or absent that, biggest AIRIS uncertainty". This shows direct AIRIS-derived signal use, not paraphrase.
• Curiosity-driven exploration. nace.py:69-85 uses airis_score to choose between exploration and exploitation, including a printed CURIOUS behavior label at nace.py:84; nace.py:71-72 applies thresholds (airis_score >= 0.9) and revisit conditions (airis_score == 1.0) for goal-directed action selection.
• NAL frequency/confidence truth-values. README.md:5-9 + the planner: hypothesis truth values use NAL (frequency, confidence) pairs (paradigm-distinct from PLN's (strength, count); mirror of S1 V1-4 [AIRIS-CONFIDENCE-NOT-PLN-TV]).
• AIRIS comparison anchors. nace.py:403, :408, :442 contain explicit comparison-to-classical-AIRIS-behavior code paths — confirming NACE positions itself as an extension/comparison study, not a re-implementation.
• MeTTa bridge surface. bridge.py + spaces.metta / knowledge.metta / tasks.metta / input.metta connect NACE to a MeTTa runtime via the ONA (OpenNARS for Applications) bridge surface — one of the world-mode interaction paths, not the whole engine.

Implementation Surface

Author: Patrick Hammer (patham9). NACE is part of patham9's "non-axiomatic" portfolio together with MeTTa-NARS and Hammer's co-authorship on the AIRIS paper (Cook & Hammer 2024).

Cluster-Narrative Position

• vs AIRIS: Inheritance/extension, not identity. NACE explicitly extends AIRIS to partial-observability + nonstationary + external-change settings + adds NAL evidence revision. The closed S1 paradigm-distinct verdicts (V1-3 [AIRIS-CURIOSITY-NOT-ECAN], V1-4 [AIRIS-CONFIDENCE-NOT-PLN-TV], V1-5 [AIRIS-STATE-GRAPH-NOT-ATOMSPACE]) carry forward to NACE.
• vs MeTTa-NARS: Shared author (patham9), shared NAL truth-value semantics (f/c). Different paradigms: NACE is a causal-rule learning agent that uses NAL evidence; MeTTa-NARS is a faithful NAL-1..NAL-5 reasoner port to MeTTa. NACE bridges TO MeTTa-NARS / ONA via bridge.py; it is not a NARS implementation.
• vs PLN (closed cluster): Paradigm-distinct. NAL f/c ≠ PLN s/c. Cross-link as boundary, not as alternative implementation.
• vs ECAN (closed cluster): Paradigm-distinct. NACE curiosity drives exploration locally via airis_score; ECAN attention is a global-economic STI/LTI dynamic. Not the same mechanism.
• vs MOSES, AI-DSL, Concept Blending, Pattern Mining (HAA clusters): Adjacent but non-integrated; no cross-imports at HEAD.

What This Card Is Not

• Not a NARS implementation. See MeTTa-NARS for that. NACE uses NAL evidence values but does not implement NAL-N inference rules.
• Not an AIRIS clone. See AIRIS. NACE extends AIRIS to a strictly larger problem class; the original AIRIS apparatus is referenced/compared, not re-implemented.
• Not C++. The repo is 100% Python at HEAD. Any "C++" / src/main.cpp / NACE.cpp claim originates from a pre-cluster-pilot reviewer confabulation rejected at S5 close (V5-1).
• Not part of the OpenCog/Hyperon-core stack. NACE is a standalone Hammer-lineage research engine. Its MeTTa connection is via the bridge.py ONA bridge surface, not deep AtomSpace/PLN integration.

Status and Sources

Implementation status: Active maintained research line. Recent commit theme is Qt/Wayland support (PyQt GUI). Demonstrates AIRIS-derived control on grid-world environments with Non-Axiomatic evidence tracking.

Primary sources:

• Hammer, P. (n.d.). NACE: Non-Axiomatic Causal Explorer. README + repository at patham9/NACE.
• Cook, B. & Hammer, P. (2024). AIRIS: Autonomous Intelligent Reinforcement Inferred Symbolism. KTH/DiVA diva2:1890142. Source paper for the AIRIS apparatus that NACE extends.
• Wang, P. (2013). Non-Axiomatic Logic: A Model of Intelligent Reasoning. World Scientific. Source for NAL frequency/confidence semantics that NACE uses for evidence tracking.

Cluster-pilot extraction archive: scripts/archive/non_clustered_haa_pilot/source5_NACE_AIDSL_MOSES_MeTTaNARS/ (close 2026-05-07). V5-1 [NACE-IMPLEMENTATION-BACKED-CORE-PURE-PYTHON] + V5-2 [NACE-AIRIS-DERIVED-NAL-ADJACENT] + V5-3 [NACE-BRIDGES-METTA-NARS-NOT-SAME] + V5-13 [PATHAM9-HAA-PORTFOLIO] carry-forwards locked at S5 close.