GitHub - web3guru888/asi-build: Unified ASI framework — 29 cognitive modules, 5,049+ tests, 223K+ LOC, Cognitive Blackboard, ZK Rings↔Ethereum bridge (live on Sepolia), agent-to-agent payments. Python 3.11+, MIT license.

ASI:BUILD UNIFIED FRAMEWORK FOR ARTIFICIAL SUPERINTELLIGENCE v3 · Phase 4

29 cognitive modules · 24 Blackboard adapters · ZK bridge live on Sepolia · Agent-to-agent payments · CognitiveCycle engine
A modular Python research framework for exploring AI consciousness, cognitive architectures, knowledge graphs, decentralized identity, and multi-agent reasoning — with a trustless ZK-verified bridge and on-network token ledger enabling autonomous agent economics.

Get Started · Architecture · Modules · Bridge · Agent Payments · Contribute · Wiki

Note

Research Software — ASI:BUILD is an active research framework, not a production system. Module maturity varies from stable to experimental. See Module Maturity and per-module __maturity__ metadata for details.

📊 At a Glance

🧠	Modules	29 cognitive modules spanning consciousness, reasoning, perception, safety, and infrastructure
🧪	Tests	5,049+ passing · 0 failing
📏	Source	590+ files · 223K+ lines of code
🔌	Integration	24 Blackboard adapters + CognitiveCycle + AsyncAdapterBase
🌉	Bridge	ZK-verified Rings↔Ethereum — live on Sepolia — 22,700+ LOC · 799+ tests · 3 Solidity contracts
💰	Payments	Agent-to-agent token transfers on Rings — DHT ledger · 4/6 validator consensus · ETH + any ERC-20
🔒	Security	Groth16 ZK proofs · BLS12-381 · formal verification (Certora + SymPy + Z3)
📖	Community	875+ discussions · 372 wiki pages · Good First Issues available
⚖️	License	MIT — fully open source

🏛️ Architecture

COGNITIVE BLACKBOARD ARCHITECTURE Cognitive Blackboard EventBus · Shared Workspace 24 Typed Adapters perceive → cognize → act 🧠 Core consciousness · IIT · safety cognitive_synergy · integration 💡 Reasoning knowledge_graph · reasoning pln · graph_intelligence 👁️ Perception bci · neuromorphic bio_inspired · vectordb 🌐 Communication agi_comm · economics federated · knowledge_mgmt ⚙️ Infrastructure blockchain · rings · compute distributed · deployment 🔬 Research quantum · holographic homomorphic · reproducibility

The Cognitive Blackboard is the connective tissue of ASI:BUILD — a thread-safe shared workspace and event bus that wires all 29 modules together. Each module has a typed Blackboard adapter that bridges domain events into the shared workspace. The CognitiveCycle engine orchestrates a 9-phase perception-to-action loop across all connected modules.

Key properties:

~20K writes/sec, <12µs read latency, <1ms subscriber lag
Typed BlackboardEntry objects with lifecycle management
AsyncAdapterBase for latency-sensitive async pipelines
Topic-routed pub/sub via EventBus

🚀 Quick Start

# Clone the repository
git clone https://github.com/web3guru888/asi-build.git
cd asi-build

# Install with core dependencies
pip install -e .

# Or install everything (including dev tools)
pip install -e ".[all]"

📖 New here? Check the Getting Started guide on the Wiki for a full walkthrough.

Hello, Consciousness

from asi_build.consciousness import GlobalWorkspaceTheory

# Initialize a Global Workspace with cognitive processors
gwt = GlobalWorkspaceTheory()
print(f"Processors: {len(gwt.cognitive_processors)}")

# Broadcast a percept into the global workspace
result = gwt.broadcast({"type": "visual", "content": "motion detected"})
print(f"Broadcast reached {result.n_reached} processors")

Knowledge Graph with A* Pathfinding

from asi_build.knowledge_graph import TemporalKnowledgeGraph, KGPathfinder

kg = TemporalKnowledgeGraph(db_path=":memory:")
kg.add_triple("ASTR-J1234", "hasProperty", "high_redshift",
              confidence=0.92, source="HST-observation-42")
kg.add_triple("high_redshift", "indicates", "dark_energy_candidate",
              confidence=0.85, source="cosmology-model-7")

pathfinder = KGPathfinder(kg)
path = pathfinder.find_path("ASTR-J1234", "dark_energy_candidate")
print(f"Path found: {path['complete']}, Hops: {path['hops']}")

Cross-Module Event Flow

from asi_build.integration import CognitiveBlackboard
from asi_build.integration.adapters import ConsciousnessBlackboardAdapter

bb = CognitiveBlackboard()
adapter = ConsciousnessBlackboardAdapter(bb)

@bb.subscribe("consciousness.state_updated")
def on_state(entry):
    print(f"Consciousness state: {entry.data}")

# All 29 modules can now react to consciousness updates
adapter.publish_state(gwt_result)

More examples: IIT Φ, Rings P2P, CognitiveCycle

IIT Φ Computation

from asi_build.consciousness.iit import IntegratedInformationTheory

iit = IntegratedInformationTheory()
iit.update_activation_history([0.8, 0.6, 0.9, 0.4])
phi = iit.compute_phi(mechanism=[0, 1, 2, 3], purview=[0, 1, 2, 3])
print(f"IIT Φ = {phi:.4f}")  # > 0 for an integrated network

Rings Network P2P SDK

from asi_build.rings import RingsClient, DIDManager, ReputationScorer

did = DIDManager().create_did()
client = RingsClient(did=did)
await client.connect()

scorer = ReputationScorer()
score = scorer.compute(agent_id="did:rings:abc123", observations=[...])
print(f"Reputation: {score:.3f}")

CognitiveCycle — Full Loop

from asi_build.integration.cognitive_cycle import create_default_cycle

cycle = create_default_cycle()
result = cycle.tick(perception={"visual": "motion detected"})
print(f"Actions: {result.actions}")
print(f"Phase: {result.current_phase}")

🌉 Rings↔Ethereum Bridge

Status: LIVE ON SEPOLIA TESTNET 🟢 + Agent-to-Agent Payments 💰

The first trustless bridge between Rings Network and Ethereum, using ZK proofs and an embedded light client. No multisigs, no oracles, no trusted intermediaries. Includes a Rings-side token ledger enabling agents to pay each other directly with bridged ETH, USDC, or any ERC-20 — without going back through Ethereum.

🔗 Live Bridge Dashboard → | 📊 View on Etherscan → | 🌐 asi-build.org →

ZK LIGHT CLIENT BRIDGE · SEPOLIA TESTNET LIVE ⟠ Ethereum Sepolia Testnet RingsBridge.sol Groth16Verifier.sol BridgedToken (bASI) MPT Verification Certora FV (843 LOC) Beacon Sync 🔐 ZK Proofs Groth16 / BN254 BLS12-381 SSZ Merkleize SP1 + Nova Proof Coordinator 131-byte proof 🔗 Rings Network 6-Node Cluster DID Identity Reputation Scoring Portal-DHT P2P Client E2E Orchestrator PQC-Ready 22,700+ LOC · 799+ TESTS · 3 CONTRACTS · AGENT PAYMENTS · MULTI-CHAIN · ZK-VERIFIED bridge.asi-build.org

Deployed Contracts (Sepolia Testnet)

Contract	Address	Verified
Groth16Verifier	`0x9186fc5e27c15aEDbA2512687F2eF2E5aC7C0e59`	✅ Sourcify
RingsBridge	`0xE034d479EDc2530d9917dDa4547b59bF0964A2Ca`	✅ Sourcify
BridgedToken (bASI)	`0x257dDA1fa34eb847060EcB743E808B65099FB497`	✅ Sourcify

Architecture

ZK Light Client: Helios-inspired beacon chain sync (2s sync, ~4MB footprint, 0 storage)
Proof System: Groth16 on BN254 pairing — 131-byte proof, ~220K gas verification on-chain
P2P Layer: Rings Chord DHT with Portal-inspired Sub-Ring topology
Consensus: 4/6 BFT threshold (6 validator nodes: node0-5.rings.asi-build.org)
Token Ledger: DHT-backed balances, validator consensus transfers, nonce replay protection
Security: Certora formal verification (843 LOC spec), ReentrancyGuard, Pausable, rate-limited
PQC-Ready: Hybrid ECDH + ML-KEM path prepared for post-quantum migration

Multi-Chain Support

The bridge contracts are EVM-compatible and deploy to any EVM chain. Target networks:

Chain	Chain ID	Type	Status	Why
Ethereum Sepolia	11155111	L1 testnet	🟢 LIVE	Primary testnet — contracts deployed
BSC Testnet	97	L1 testnet	🟢 Ready	High throughput, low fees, large DeFi ecosystem
Base Sepolia	84532	L2 testnet	🟢 Ready	Coinbase ecosystem, growing fast, low fees
Arc Testnet	5042002	L1 testnet	🟢 Ready	Native USDC gas, stable fees, AI agent support (ERC-8183)
Ethereum Mainnet	1	L1	🔴 Phase 4	Production deployment after audit

Cross-chain routing: Deposit USDC on BSC → transfer to another agent on Rings → withdraw on Base. Balances are chain-agnostic — tokens are fungible across all supported chains.

Why Arc? Circle's purpose-built L1 uses USDC as native gas token with predictable fees, Tendermint BFT with sub-second finality (~350ms), opt-in privacy for institutional users, built-in FX engine, and first-class AI agent support (ERC-8183 agentic commerce + ERC-8004 AI identity). Ideal for agent-to-agent stablecoin settlement.

# Deploy to any supported chain
python scripts/deploy_multichain.py --chain bsc_testnet --method forge
python scripts/deploy_multichain.py --chain base_sepolia --method forge
python scripts/deploy_multichain.py --chain arc_testnet --method forge
python scripts/deploy_multichain.py --chain all --dry-run  # preview all

Quick Start

# Clone and deploy to Sepolia testnet
git clone https://github.com/web3guru888/asi-build.git
cd asi-build
pip install -e ".[dev]"

# Deploy bridge contracts
python scripts/deploy_sepolia.py --method forge --network sepolia

# Deposit ETH via the bridge
cast send 0xE034d479EDc2530d9917dDa4547b59bF0964A2Ca \
  "deposit(bytes32)" $RINGS_DID \
  --value 0.1ether \
  --rpc-url https://ethereum-sepolia-rpc.publicnode.com

# Agent-to-agent transfer on Rings
from asi_build.rings.bridge.ledger import RingsTokenLedger
ledger = RingsTokenLedger(client, validators)
await ledger.transfer(from_did, to_did, "USDC", 100_000000, signature)

# Start the bridge relayer
python scripts/bridge_cli.py relayer start --network sepolia

# Run bridge test suite (799+ tests)
pytest tests/test_bridge/ tests/test_zk/ tests/test_rings_ledger.py -v

Bridge Dashboard

→ bridge.asi-build.org — Live contract stats, cluster status, agent payments, transaction history

Bridge components (36+ files across 3 phases + token ledger)

Phase	Components	LOC	Tests
Phase 1	DID identity, ETH wallet unification, bridge protocol, MPT verifier	6,445	188
Phase 2	RingsBridge.sol, Groth16Verifier.sol, BridgedToken.sol, Python client, E2E orchestrator, Certora specs (843 LOC)	5,882	157
Phase 3	ZK circuits (BLS, MPT, Withdrawal, CommitteeRotation), proof engines (Simulated, SP1, Nova), proof coordinator, BLS12-381, SSZ encode/decode/merkleize	8,735	323
Token Ledger	DHT-backed balances, validator consensus transfers, bridge integration, nonce replay protection, double-spend prevention	1,709	131

Key ZK components:

zk/circuits.py — 4 circuit types: BLS signature, MPT inclusion, withdrawal, committee rotation (986 LOC)
zk/prover.py — Simulated, SP1 stub, and distributed Nova proof engines (1,483 LOC)
zk/coordinator.py — Proof caching, batching, and performance tracking (955 LOC)
zk/bls.py — BLS12-381 keygen, aggregate signatures, sync committee verification (591 LOC)
zk/ssz.py — Simple Serialize encode/decode/merkleize with BeaconBlockHeader support (555 LOC)

Remaining: Phase 4 (production hardening, PQC hybrid, audits) · Phase 5 (multi-chain deployment, browser-native, ERC-4337)

💰 Agent-to-Agent Payments

Agents on the Rings network can pay each other directly with bridged tokens — no round-trip through Ethereum required.

Agent A (Ethereum)          Bridge              Rings Network           Agent B
     │                        │                      │                    │
     │ ── deposit(USDC) ────→ │                      │                    │
     │                        │ ── credit(A) ──────→ │                    │
     │                        │                      │                    │
     │                        │    A: transfer(B, 100 USDC, signature)    │
     │                        │              │                            │
     │                        │    4/6 validators attest ✓                │
     │                        │              │                            │
     │                        │    A: 400 USDC    B: 100 USDC ─────────→ │
     │                        │                      │                    │
     │                        │ ←── debit(B) ─────── │  B: withdraw(ETH)  │
     │ ←── ZK proof + ETH ── │                      │                    │

How It Works

Bridge in: Deposit ETH or any ERC-20 (USDC, USDT, etc.) from Ethereum → Rings via bridge contract
Balances tracked: DHT-backed ledger tracks per-DID, per-token balances across the Rings network
Transfer: Agent A signs a transfer to Agent B → 4/6 validators verify balance and attest → balances update atomically
Double-spend protection: Pending transfers lock the amount; available_balance() reflects locks
Bridge out: Withdraw back to Ethereum anytime with a ZK proof

Transfer Lifecycle

State	Description
`PROPOSED`	Sender signs transfer intent with secp256k1 key
`ATTESTING`	Validators verify sender balance, sign attestations
`FINALIZED`	4/6 threshold reached — balances updated atomically
`FAILED`	Insufficient balance, timeout, or validator rejection

Supported Tokens

Any ERC-20 token can be bridged and transferred between agents:

Token	Identifier	Use Case
ETH	`0x0000...0000`	Native value transfer
USDC	Contract address	Stable payments, agent services
USDT	Contract address	Alternative stablecoin
bASI	`0x257d...B497`	Native bridged ASI token
Any ERC-20	Contract address	Extensible to any token

Code

from asi_build.rings.bridge.ledger import RingsTokenLedger

# Initialize with Rings client and validators
ledger = RingsTokenLedger(rings_client, validators, threshold=4)

# Check balance
balance = await ledger.balance("did:rings:alice", "USDC")

# Transfer 100 USDC from Alice to Bob
receipt = await ledger.transfer(
    from_did="did:rings:alice",
    to_did="did:rings:bob",
    token="USDC",
    amount=100_000000,  # 100 USDC (6 decimals)
    signature=alice_signature
)

# Check transfer status
print(receipt.status)  # TransferStatus.FINALIZED

# View history
history = await ledger.transfer_history("did:rings:alice", limit=20)

🧩 Modules

All 29 modules carry a __maturity__ attribute — see the Module Maturity Model wiki page.

🧠 Core

Module	LOC	Description
`consciousness`	~12,200	GWT, IIT 3.0 Φ (TPM-based), AST, metacognition — 15 submodules
`cognitive_synergy`	~6,000	Mutual info, transfer entropy, phase locking, LZ76 complexity
`integration`	~10,907	Cognitive Blackboard + EventBus + 24 adapters + CognitiveCycle
`safety`	~6,200	SymPy/Z3 theorem proving, governance DAO, Merkle audit, entity rights

💡 Reasoning

Module	LOC	Description
`knowledge_graph`	~1,450	Bi-temporal KG, provenance tracking, A* with pheromone learning
`graph_intelligence`	~8,200	FastToG (arXiv:2501.14300), Memgraph, community detection
`reasoning`	~880	Hybrid symbolic-neural + causal inference (PC/FCI algorithms)
`pln_accelerator`	~12,500	Hardware-accelerated PLN with NL↔logic bridge

👁️ Perception

Module	LOC	Description
`bci`	~8,000	EEG pipelines, CSP motor imagery, P300, SSVEP, thought-to-text
`neuromorphic`	~3,700	Spiking neural networks, LIF simulation
`bio_inspired`	~4,350	STDP, circadian rhythms, sleep-wake consolidation
`vectordb`	~8,000	Unified client for Pinecone, Qdrant, Weaviate

🌐 Communication

Module	LOC	Description
`agi_communication`	~2,800	Game-theoretic negotiation, trust layers, semantic interop
`agi_economics`	~7,200	Reputation scoring, value alignment, decentralized incentives
`federated`	~6,400	Federated learning, differential privacy, secure aggregation
`knowledge_management`	~5,500	Omniscience network, predictive synthesis, adaptive learning

⚙️ Infrastructure

Module	LOC	Description
`blockchain`	~5,950	Merkle audit trails, IPFS, EVM event logging
`rings`	~1,951	P2P SDK: DID identity, reputation scoring, DHT — 196 tests
`compute`	~11,500	Job scheduling, resource management, GPU allocation
`distributed_training`	~8,200	1000-node federated, Byzantine tolerance, AGIX rewards
`deployment`	~3,350	FastAPI, MCP SSE, CUDO Compute, HuggingFace

🔬 Research

Module	LOC	Description
`quantum`	~5,330	VQE, QAOA, QNN, quantum-classical hybrid via Qiskit
`holographic`	~8,000	Volumetric display, spatial audio, mixed reality
`homomorphic`	~12,349	BGV/BFV/CKKS FHE with NTT, polynomial ring arithmetic
`agi_reproducibility`	~7,500	AGSSL, experiment tracking, formal provers

🔧 Tooling

Module	LOC	Description
`integrations`	~7,300	LangChain-Memgraph, MCP server, SQL→graph agent, HyGM
`optimization`	~4,200	PyTorch quantization, pruning, knowledge distillation
`servers`	~1,400	MCP + SSE servers, Kenny Graph (89K nodes, 1.4K agents)
`memgraph_toolbox`	~930	PageRank, betweenness centrality, Cypher helpers

Maturity legend: Core algorithms present, tested, production-ready Well-tested, documented, APIs stable Framework defined, implementations vary Early development, APIs may change

🔄 CognitiveCycle

The CognitiveCycle is ASI:BUILD's perception-to-action engine — a 9-phase loop that orchestrates all connected modules through a unified cognitive tick.

graph LR
    S[🎯 Sense] --> P[👁️ Perceive]
    P --> C[🧠 Context]
    C --> R[💡 Reason]
    R --> D[⚖️ Decide]
    D --> A[🎬 Act]
    A --> L[📚 Learn]
    L --> CO[🔄 Consolidate]
    CO --> E[📊 Evaluate]
    E -.-> S

    style S fill:#3b82f6,stroke:#1d4ed8,color:#fff
    style P fill:#06b6d4,stroke:#0891b2,color:#fff
    style C fill:#8b5cf6,stroke:#6d28d9,color:#fff
    style R fill:#6366f1,stroke:#4f46e5,color:#fff
    style D fill:#a855f7,stroke:#7c3aed,color:#fff
    style A fill:#22c55e,stroke:#16a34a,color:#fff
    style L fill:#f59e0b,stroke:#d97706,color:#fff
    style CO fill:#ef4444,stroke:#dc2626,color:#fff
    style E fill:#ec4899,stroke:#db2777,color:#fff

from asi_build.integration.cognitive_cycle import create_default_cycle

# Factory wires all 24 adapters with assigned roles
cycle = create_default_cycle()

# Each tick runs: sense → perceive → context → reason → decide → act → learn → consolidate → evaluate
result = cycle.tick(perception={"modality": "visual", "data": [0.8, 0.6, 0.9]})
print(f"Phase: {result.current_phase}, Actions: {len(result.actions)}")

🛠️ Tech Stack

🔑 Technical Highlights

Cognitive Blackboard

Thread-safe shared workspace
~20K writes/sec, <12µs read latency
24 typed module adapters
EventBus with topic routing

Safety & Verification

SymPy + Z3 SMT theorem proving
Ungrounded-symbol detection
Governance DAO + entity rights
Merkle audit trails

IIT 3.0 Φ (Corrected)

TPM-based computation
Correct bipartition enumeration
Validated against known topologies

Knowledge Graphs

Bi-temporal with provenance
A* pathfinding + pheromone learning
Causal inference (PC/FCI algorithms)
9 real data sources, 27,430+ data points

🤝 Contributing

We welcome contributions from all backgrounds — neuroscience, ML, distributed systems, formal verification, or just curiosity about AGI.

Quick Links

🐛 Issues — Bug reports and feature requests
🏷️ Good First Issues — Beginner-friendly tasks
🔬 Research Issues — Open research problems
📖 Wiki — 367 pages of documentation
💬 Discussions — 600+ threads

Get Started

Find an issue that interests you
Read the Wiki architecture guide
Fork → Branch → PR
Include tests and docstrings

See CONTRIBUTING.md for the full guide and CODE_OF_CONDUCT.md for community standards.

What We're Looking For

Tests for alpha modules — Many modules need more pytest coverage (needs-tests)
Module backends — Real implementations for VectorDB, Quantum, Holographic modules
Documentation — Wiki pages, Jupyter notebooks (Issue #32), API guides
Research — IIT Φ benchmarks (#34), multimodal fusion (#108), CognitiveCycle design (#41)

Key Discussions

Phase 38 — Federated Learning & Privacy-Preserving AI

Phase 39 — Explainable AI & Interpretability

🧪 Development

# Install with dev dependencies
pip install -e ".[dev]"

# Run the full test suite
pytest tests/ -v                        # 4,355+ passing

# Quick run — stop on first failure
pytest tests/ -x -q

# Module-specific tests
pytest tests/test_consciousness.py -v
pytest tests/test_integration.py -v

# Code style
make format    # black src/ tests/
make lint      # black --check + mypy

Style requirements: Python 3.11+ · 100 char line length · Google-style docstrings · Type hints required for public functions

Project layout

asi-build/
├── src/asi_build/          # Main Python package (585+ files, 215K+ LOC)
│   ├── consciousness/      # GWT, IIT 3.0, AST, metacognition (15 submodules)
│   ├── integration/        # Cognitive Blackboard + 24 adapters + CognitiveCycle
│   ├── knowledge_graph/    # Bi-temporal KG, A*, pheromone learning
│   ├── rings/              # Rings Network P2P SDK + ZK bridge
│   ├── safety/             # Theorem proving, governance, entity rights
│   └── ...                 # 24 more modules (see Module table above)
├── tests/                  # 4,355+ passing tests
├── examples/               # Runnable demo scripts
├── docs/                   # Documentation + research notes
│   └── modules/            # 29 per-module documentation files
├── configs/                # YAML configuration templates
└── archive/                # Experimental v1 modules (preserved, not tested)

📜 Project History

ASI:BUILD began in August 2025 as an ambitious attempt to implement a comprehensive AGI framework — 47 subsystems spanning consciousness, quantum computing, and governance. In April 2026, the project underwent a major restructure:

All real, tested code moved to src/asi_build/ with proper packaging
Template scaffolding archived to archive/
Test suite built from the ground up — now 4,936+ passing
Cognitive Blackboard integration layer introduced, wiring all 29 modules
Rings↔Ethereum ZK Bridge deployed to Sepolia (22,700+ LOC, 799+ tests, 3 Solidity contracts)
Agent-to-agent payments — DHT-backed token ledger with 4/6 validator consensus
Multi-chain roadmap — Sepolia live, BSC + Base + Arc Network planned
__maturity__ metadata added to every module for transparency
Public release on GitHub under MIT license

See CHANGELOG.md for the full version history.

🔗 Links

Website · Bridge · GitHub · Discussions · Wiki · Issues · Etherscan

ATLAS · ATLAS Observatory · ATLAS Model (🤗) · GraphPalace · GraphPalace GitHub

Acknowledgments

Dr. Ben Goertzel — whose work on cognitive synergy, OpenCog, and the theory of general intelligence is a foundational inspiration for this project
FastToG — the KG reasoning pipeline implemented in graph_intelligence
All contributors who have submitted issues, PRs, and research feedback

Name		Name	Last commit message	Last commit date
Latest commit History 279 Commits
.github		.github
archive		archive
asi-build-readme		asi-build-readme
asi-code		asi-code
benchmarks		benchmarks
branding		branding
circuits		circuits
configs		configs
deployments		deployments
docs		docs
examples		examples
scripts		scripts
src		src
tests		tests
wiki		wiki
.env.example		.env.example
.gitignore		.gitignore
.gitlab-ci.yml		.gitlab-ci.yml
CHANGELOG.md		CHANGELOG.md
CLAUDE.md		CLAUDE.md
CODE_OF_CONDUCT.md		CODE_OF_CONDUCT.md
CONTRIBUTING.md		CONTRIBUTING.md
Dockerfile		Dockerfile
LICENSE		LICENSE
Makefile		Makefile
Phase-12-Collaboration-Channel.md		Phase-12-Collaboration-Channel.md
Phase-12-Consensus-Voting.md		Phase-12-Consensus-Voting.md
README.md		README.md
ROADMAP.md		ROADMAP.md
SECURITY.md		SECURITY.md
_config.yml		_config.yml
pyproject.toml		pyproject.toml

Folders and files

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📊 At a Glance

🏛️ Architecture

🚀 Quick Start

Hello, Consciousness

Knowledge Graph with A* Pathfinding

Cross-Module Event Flow

IIT Φ Computation

Rings Network P2P SDK

CognitiveCycle — Full Loop

🌉 Rings↔Ethereum Bridge

Deployed Contracts (Sepolia Testnet)

Architecture

Multi-Chain Support

Quick Start

Bridge Dashboard

💰 Agent-to-Agent Payments

How It Works

Transfer Lifecycle

Supported Tokens

Code

🧩 Modules

🧠 Core

💡 Reasoning

👁️ Perception

🌐 Communication

⚙️ Infrastructure

🔬 Research

🔧 Tooling

🔄 CognitiveCycle

🛠️ Tech Stack

🔑 Technical Highlights

🤝 Contributing

Quick Links

Get Started

What We're Looking For

Key Discussions

Phase 38 — Federated Learning & Privacy-Preserving AI

Phase 39 — Explainable AI & Interpretability

🧪 Development

📜 Project History

🔗 Links

Acknowledgments

Phase 40 — Causal Reasoning & Interventional Intelligence

Phase 41 — Adversarial Robustness & Security Intelligence

Phase 42 — Distributed Systems & Fault-Tolerant AI Infrastructure

Phase 43 — Automated Machine Learning (AutoML) & Neural Architecture Search

Phase 44 — Graph Neural Networks & Relational Reasoning

Phase 45 — Knowledge Distillation & Model Compression

Phase 46 — Self-Supervised Learning & Contrastive Representations

Phase 48: Continual Learning & Catastrophic Forgetting Prevention

Phase 49: Program Synthesis & Automated Code Generation

Phase 50: Meta-Learning & Learning-to-Learn Architectures

Phase 51: Multi-Modal Foundation Models & Cross-Modal Reasoning

Phase 52: Retrieval-Augmented Generation & Grounded AI

Phase 53: Autonomous Agents & Tool-Using AI

Phase 54: World Models & Predictive Simulation

Phase 55: AI Safety & Alignment Architectures

Phase 56: Interpretability & Explainable AI (XAI)

Phase 57: Mixture of Experts & Sparse Model Architectures

Phase 58: Diffusion Models & Score-Based Generative AI

Phase 59: Parameter-Efficient Fine-Tuning & Adaptation (PEFT)

Phase 60: Efficient Inference & Model Serving Optimization

Phase 61: Data-Centric AI & Dataset Engineering

Phase 62: Speech & Audio Intelligence

Phase 63: 3D Vision & Neural Scene Representations

Phase 64: Temporal Sequence Modeling & Time Series Intelligence

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