CLE-Net
Contents:
Getting Started
Glossary
A
Agent
Atom
B
Blockchain Layer
C
CLE
CLE-Net
Consensus
Context
Contradiction
D
Decay
Discovery
E
Event
Evidence
G
Genesis State
I
Independence
Independence Score
K
Knowledge Graph
L
Ledger
Logic Form
M
Mining
N
Node
P
PoC
Predicate
R
Rule
Rule Candidate
Rule Cluster
Rule Commit
S
Semantic Atomizer
Symbol
Symbolic Regression
Symbolic Reasoning
Enhanced Symbolic Regression
Genetic Programming (GP)
Temporal Pattern Recognition
Uncertainty Quantification
Multi-Modal Input
Full-Duplex Interaction
OCR (Optical Character Recognition)
Graph RAG
T
Temporal Graph
Threshold
V
Validation
W
Watchdog
Related Documents
Architecture Documentation
System Overview
1. Introduction
1.1 Core Philosophy
1.2 What CLE-Net Is Not
1.3 What CLE-Net Is
2. High-Level Architecture
3. Core Layers
3.1 Human Interaction Layer
3.2 CLE Agent Layer
3.3 Cognitive Graph Layer
3.4 Blockchain / Consensus Layer
3.5 Distributed Node Layer
4. Data Flow
4.1 Forward Flow (Knowledge Discovery)
4.2 Feedback Flow (Learning)
5. Key Innovations
5.1 Symbolic + Neural Hybrid
5.2 Proof of Cognition
5.3 Contradiction as Signal
5.4 Persistence Through Transformation
6. Limitations
6.1 Current Limitations
6.2 Fundamental Limitations
7. Next Steps
Agent Architecture
1. Overview
2. Agent Components
2.1 Input Handlers
2.2 Event Stream
2.3 Semantic Atomizer
2.4 Symbol Mapper
2.5 Symbolic Regression Engine
2.6 Enhanced Symbolic Regression ✅ PHASE 3 - COMPLETED
2.7 Multi-Modal Input Processing ✅ PHASE 3 - COMPLETED
2.6 Rule Manager
2.7 Consensus Engine
2.8 Blockchain Interface
3. Agent State
3.1 Local State Structure
3.2 State Persistence
3.3 State Migration
4. Agent Lifecycle
5. Configuration
5.1 Core Parameters
6. Failure Modes
6.1 Crash Recovery
6.2 Network Partition
6.3 Data Corruption
7. Security
7.1 Agent Identity
7.2 Communication Security
8. Related Documents
Proof of Cognition (PoC) Consensus Model
1. Motivation
2. Core Idea: Proof of Cognition
2.1 Intuition
2.2 Formal Definition
3. Key Concepts
3.1 Cognitive Agent (Node)
3.2 Rule Candidate
3.3 Rule Commitment
3.4 Rule Matching
4. Consensus Conditions
4.1 Mandatory Conditions
4.2 Independence Score
4.3 Confidence Calculation
5. Contradiction Handling
5.1 Contradictions Are Signals
5.2 Handling Process
5.3 Context Separation
5.4 Confidence Decay
6. Incentive Mechanism
6.1 Mining = Thinking
6.2 Reward Function
6.3 Sybil Resistance
7. Formal Specification
7.1 Consensus Algorithm
7.2 Acceptance Criteria
8. Why PoC Is Different
9. Limitations
9.1 Known Weaknesses
9.2 Mitigation Strategies
9.3 Honest Acknowledgment
10. Implementation Notes
10.1 Message Types
10.2 Performance Considerations
10.3 Monitoring Metrics
11. Related Documents
Threat Model
1. Security Philosophy
1.1 Explicit Non-Goals
1.2 What CLE-Net Does Guarantee
1.3 Why This Honesty Matters
2. System Assets
2.1 Primary Assets (Must Protect)
2.2 Secondary Assets (Should Protect)
3. Adversary Model
3.1 Assumed Capabilities
3.2 Not Assumed
4. Threat Categories
T1: Single Malicious Agent
T2: Rule Spam Attack
T3: Sybil Attack (Critical Analysis)
T4: Coordinated False Consensus
T5: Data Poisoning
T6: Blockchain-Level Attacks
T7: Privacy Leakage
T8: Model Exploitation
T9: Emergent Harmful Rules
5. Attack Surface Summary
6. Security Principles Applied
6.1 Defense in Depth
6.2 Transparency Over Illusion
6.3 Failure Tolerance
7. Mitigation Priorities
7.1 High Priority
7.2 Medium Priority
7.3 Ongoing
8. GitHub-Ready Statement
9. Critical Reality Check
10. Related Documents
Cosmos SDK Integration
CLE-Net Cosmos SDK Architecture
Overview
Why Cosmos SDK?
✅ Advantages
❌ Rejected Alternatives
Architecture Diagram
Module Structure
1. Cognitive Module (
core/cosmos/x/cognitive/
)
2. Laws Module (
core/cosmos/x/laws/
)
3. Consensus Module (
core/cosmos/x/consensus/
)
On-Chain State
Cognitive State Block (CSB)
Cognitive Law
Cognitive Contribution Score (CCS)
Validator Information
Consensus Mechanism
Proof of Cognition (PoC)
Tendermint BFT Integration
Off-Chain Processing
On-Chain (Consensus)
Off-Chain (Computation)
Migration Path
Phase 1: Cosmos SDK v1 (Current)
Phase 2: Custom Chain (Future)
Phase 3: IBC Integration (Future)
Security Considerations
Validator Security
Law Security
Network Security
Performance Considerations
Throughput
Latency
Storage
References
Next Steps
CLE-Net Validator Roles
Overview
Validator Roles
1. Cognitive Miner
2. State Validator
3. Conflict Resolver
4. Watchdog
Validator Registration
Registration Process
Registration Example
Role Changes
Validator Rewards
CCS Distribution
Reward Calculation
Reward Distribution
Validator Slashing
Slashing Conditions
Slashing Penalties
Slashing Example
Validator Governance
Voting Rights
Voting Process
Voting Example
Validator Requirements Summary
Next Steps
References
CLE-Net Migration Path
Overview
Phase 1: Cosmos SDK v1 (Current)
Status
Description
Architecture
Features
Technical Stack
Limitations
Timeline
Exit Criteria
Decision Point: Phase 2
Phase 2: Custom Chain (Future)
Status
Description
Architecture
Features
Technical Stack
Key Improvements
Migration Strategy
Timeline
Exit Criteria
Decision Point: Phase 3
Phase 3: IBC Integration (Future)
Status
Description
Architecture
Features
Technical Stack
Key Improvements
IBC Use Cases
Migration Strategy
Timeline
Exit Criteria
Migration Decision Matrix
Recommendations
For Phase 1 (Current)
For Phase 2 (Future)
For Phase 3 (Future)
Risks and Mitigations
Phase 1 Risks
Phase 2 Risks
Phase 3 Risks
Conclusion
References
Protocol Documentation
CLE-Net Protocol Specification: Message Formats
1. Overview
2. Message Envelope
Envelope Fields
3. Message Types
3.1 Rule Commit Message
3.2 Challenge Message
3.3 Confirm Message
3.4 Query Message
3.5 Response Message
3.6 Error Message
3.7 State Sync Message
3.8 Gossip Message
4. Phase 3 Message Types ✅ NEW
4.1 Multi-Modal Input Message
4.2 Enhanced Symbolic Regression Message
4.3 Full-Duplex Control Message
5. State Models
4.1 Agent State
4.2 Rule State
4.3 Ledger State
5. Protocol Constants
6. Serialization
Example Serialization
7. Security
7.1 Signing
7.2 Verification
7.3 Encryption
8. Related Documents
CLE-Net P2P Network Layer Design
1. Overview
2. Network Topology
2.1 Hybrid Topology
2.2 Connection Types
3. Node Discovery
3.1 Bootstrap List
3.2 Discovery Protocol
3.3 Peer Exchange
4. Message Routing
4.1 Direct Routing
4.2 Gossip Routing
4.3 Routing Table
5. Gossip Protocol
5.1 Message Types
5.2 Gossip Message Format
5.3 Gossip Algorithm
5.4 Anti-Entropy
6. State Synchronization
6.1 Sync Protocol
6.2 Checkpoint Format
7. Connection Management
7.1 Connection Lifecycle
7.2 Handshake Protocol
7.3 Heartbeat
8. Security
8.1 Node Authentication
8.2 Message Signing
8.3 Flood Prevention
9. Performance
9.1 Target Metrics
9.2 Scalability
10. Implementation
10.1 Core Components
11. Related Documents
Whitepaper
Abstract
Keywords
1. Introduction
1.1 The Problem with Current AI Systems
1.2 The Opportunity
1.3 Our Contribution
1.3.1 Cognitive Logic Extraction (CLE)
1.3.2 Proof of Cognition (PoC)
1.3.3 Decentralized Cognitive Persistence
1.4 Paper Structure
1.5 Key Claims
1.6 Scope and Non-Goals
Cognitive Contribution Score (CCS)
1. Purpose of CCS
2. CCS Definition
3. CCS Components
4. Law Quality Score ($Q_a$)
5. Law Survival Score ($S_a$)
6. Resolution Contribution ($R_a$)
7. Uptime Score ($U_a$)
8. Penalty Term ($P_a$)
9. CCS Decay
10. Implementation Considerations
10.1 Weight Configuration
10.2 Decay Parameters
10.3 Minimum Requirements
11. Related Documents
Law Conflict Resolution Algorithm
1. What is a Conflict?
2. Law Representation
3. Conflict Resolution Pipeline
Step 1: Detection
Step 2: Context Expansion
Step 3: Dominance Evaluation
Step 4: Resolution Decision
Step 5: Learning from Conflict
4. Formal Algorithm
5. Meta-Law Generation
6. Example Resolution
Conflict Example
Resolution Process
Generated Meta-Law
7. Properties
7.1 Convergence
7.2 No Deletion
7.3 Transparency
8. Implementation Notes
Confidence Thresholds
Dominance Thresholds
9. Related Documents
CLE-Net: Decentralized Cognitive Agent Network
A Complete Whitepaper
Abstract
Table of Contents
1. Introduction
1.1 The Problem with Current AI Systems
1.2 The Opportunity
1.3 Our Contribution
1.4 Paper Structure
2. System Architecture
2.1 High-Level Overview
2.2 Design Principles
2.3 Key Properties
3. Cognitive Logic Extraction
3.1 Overview
3.2 Event Capture
3.3 Semantic Atomization
3.4 Symbol Mapping
3.5 Symbolic Regression
3.6 Rule Representation
4. Proof of Cognition Consensus
4.1 Motivation
4.2 Core Idea
4.3 Formal Definition
4.4 Independence Requirements
4.5 Consensus Algorithm
4.6 Confidence Calculation
4.7 Comparison with Other Consensus
5. Cognitive Contribution Score
5.1 Purpose
5.2 Definition
5.3 Components
5.4 Law Quality Score
5.5 CCS Decay
6. Law Conflict Resolution
6.1 What is a Conflict?
6.2 Law Representation
6.3 Resolution Pipeline
7. P2P Network Layer
7.1 Topology
7.2 Discovery Protocol
7.3 Gossip Protocol
7.4 State Synchronization
8. Threat Model
8.1 Protected Assets
8.2 Threat Analysis
8.3 Limitations
9. Implementation
9.1 Current Status
9.2 Core Modules
9.3 Running the Demo
10. Related Work
10.1 Knowledge Graphs
10.2 Symbolic AI
10.3 Decentralized Systems
11. Limitations and Future Directions
11.1 Current Limitations
11.2 Fundamental Limitations
11.3 Future Work
12. Conclusion
References
CLE-Net
Index
Index