fix(topics): 지식 그래프 정상화 — 고아 29%→4%, 인덱스 12개·개념 문서 13편

링크 그래프 분석(6,372문서·31,623링크) 기반 최소 수정 정상화:
- [수정] Topic_CPP/Topic_C 인덱스의 링크 표기를 실제 문서 제목으로 교정
  (CPP 117건·C 68건 — [[CPP Intro]] → [[C++ Intro]] 등, 인덱스 파일 2개만 수정)
- [수정] C Tutorial 별칭에 'C' 추가 — [[c]] 60건 해소 (frontmatter 1줄)
- [신규] 고아 다발 폴더 11곳에 00_INDEX MOC 자동 생성 (Poetic_Blog_Writing 500편,
  AI_and_ML 330, Coding 200, Reasoning_Creativity 161, Frontend 146 등)
- [신규] 루트 MOC(Topics Root Index) — breadcrumb [[10_Wiki/Topics]] 47건을 별칭으로 수용
- [신규] 수요 최상위 미싱 개념 문서 13편 (깨진 링크 다발 해소):
  글쓰기 7편(리듬·감정·문체·블로그·퇴고·정서·구조) + 설계 6편(React·Software
  Architecture·ADR·CQRS·Observability·RLHF) — AI 생성 초안임을 review_reason에 명시
- 기존 문서 본문은 무수정 (인덱스 2개 링크 교정 + 별칭 1줄이 수정의 전부)

결과: 고아 1,901(29%)→314(4%), 완전고립 1,018→173, 깨진 링크 10,258→9,679

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
This commit is contained in:
Antigravity Agent
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---
id: ai-and-ml-index
title: "AI and ML Index"
category: "Index"
status: "draft"
verification_status: "conceptual"
canonical_id: ""
aliases: ["AI and ML MOC", "AI and ML 목차"]
duplicate_of: ""
source_trust_level: "B"
confidence_score: 0.90
created_at: 2026-07-11
updated_at: 2026-07-11
review_reason: "고아 문서 연결용 자동 생성 MOC — 폴더 구성 변경 시 재생성 필요"
merge_history: []
tags: ["moc", "index"]
raw_sources: []
applied_in: []
github_commit: ""
---
# [[AI and ML Index]]
## 🎯 한 줄 통찰 (One-line insight)
`Domain_Programming/AI_and_ML` 폴더의 전체 문서를 연결하는 Map of Content — 이 폴더의 지식으로 들어가는 관문.
## 📚 문서 목록 (728편)
- [['ADR-0001: Project Chronicle as Independent Module']]
- [[2014 Combat Controls Update (War Commander)]]
- [[2026 AI Visual Language Generation Paradigm Shift]]
- [[20k Skinned Instances Demo (Three.js)]]
- [[3D Gaussian Splatting (3DGS)]]
- [[ABA (Applied Behavior Analysis)]]
- [[Abstract Syntax Tree (AST)]]
- [[Academic Integrity]]
- [[ACI (Agent-Computer Interface)]]
- [[Activism]]
- [[Actor-Critic Models]]
- [[Ad-hoc Hypotheses]]
- [[Adaptive Compute (적응형 계산량 조절)]]
- [[Addiction Neuroscience]]
- [[AdSense Revenue Blog Architecture]]
- [[agargaro Open Source Libraries (Three.js Extensions)]]
- [[AI & Data Sovereignty]]
- [[AI Accountability]]
- [[AI and Narrative]]
- [[AI Answer Engine Optimization (AEO)]]
- [[AI Code Assurance (AI 생성 코드 검증)]]
- [[AI Code Review]]
- [[AI Code Review + DevSecOps]]
- [[AI Connect LLM Tool (ConnectAI)]]
- [[AI Content Production Pipeline]]
- [[AI Evaluation & Benchmarks]]
- [[AI Exploitation (Game AI 공략)]]
- [[AI for Social Good (AI4SG)]]
- [[AI Generated Code Assurance (AI 생성 코드 검증)]]
- [[AI Governance Policy (AI Usage Policy)]]
- [[AI Humanism]]
- [[AI Image Generation]]
- [[AI Image Generation & Editing Workflow]]
- [[AI Image Generation Workflow (canonical)]]
- [[AI Image Quality Optimization & Debugging]]
- [[AI Literacy]]
- [[AI Overviews and SGE (Search Generative Experience)]]
- [[AI Post-editing Tools (사후 편집)]]
- [[AI Pursuit Logic (AI 추적 논리)]]
- [[AI Safety and Alignment]]
- [[AI Search Optimization]]
- [[AI 코드 리뷰]]
- [[AI-Powered Code Analysis (Autofix + Triage)]]
- [[AI-Powered Code Analysis Tools]]
- [[AI_and_ML 폴더 시스템 메타]]
- [[Algorithmic Biology]]
- [[Algorithmic Fairness]]
- [[Algorithmic Transparency]]
- [[Amdahl's Law]]
- [[Anaemic Domain Model]]
- [[Anarchism]]
- [[Anarcho-Primitivism]]
- [[Anthropic Principle]]
- [[Anthropomorphism]]
- [[Antifragility]]
- [[API Response & State Modeling]]
- [[API Response Modeling + State Machine]]
- [[API-backed Image Generation Workflow]]
- [[Arc 2 — March 2026 Research Drop (War Commander)]]
- [[Architecture Anti-patterns]]
- [[Articulateness]]
- [[Artifacts & Infrastructure (Agentic Systems)]]
- [[Artificial Intelligence (AI)]]
- [[Artificial Life (ALife)]]
- [[Arts (Human + AI Era)]]
- [[ASD Intervention (AI-Assisted)]]
- [[Assessment (Educational + ML Evaluation)]]
- [[Asset-Specific Knowledge]]
- [[ASTRA 자기 아키텍처]]
- [[Atmospheric Intelligence (Ambient AI)]]
- [[Authenticity]]
- [[Auto-Encoding]]
- [[Automated Mapping (SLAM / HD Map)]]
- [[Automated Theorem Proving (ATP)]]
- [[Autonomous Polling & Wait Automation]]
- [[Autonomous Vehicles]]
- [[Availability and Persistence]]
- [[Awards (Recognition Systems)]]
- [[Awareness Gap (인지 공백)]]
- [[Axify (Engineering Productivity Platform)]]
- [[Axioms]]
- [[Bag of Words (BoW)]]
- [[Baiting (Game AI Tactic)]]
- [[Baseline (Web Platform Features)]]
- [[Batch Inference]]
- [[Bayesian Brain Hypothesis]]
- [[Bayesian Statistics]]
- [[BCG 2026 Global Gaming Survey]]
- [[Be Detailed (Specificity Principle)]]
- [[Beliefs]]
- [[Benchmarks (AI Evaluation)]]
- [[BERT (Bidirectional Encoder Representations from Transformers)]]
- [[Best-of-N Sampling]]
- [[Bias Correction Algorithm]]
- [[Bias vs Variance Trade-off]]
- [[Bibliometrics]]
- [[Binary Author Identification]]
- [[Binary Search]]
- [[Bioenergetics]]
- [[Biological Intelligence]]
- [[BioShock (2007) — Game AI & Environmental Narrative]]
- [[Black-Box Optimization]]
- [[Blockchain]]
- [[Blog Production Standard Manual]]
- [[Bloom Filters]]
- [[Boltzmann Machines]]
- [[Boosting Algorithms (XGBoost / LightGBM / CatBoost)]]
- [[Boss Orchestration & Gimmick Management]]
- [[Bottlenecks (Performance & Process)]]
- [[Bounded Contexts (DDD)]]
- [[Bounded Rationality]]
- [[Bounding Box Regression]]
- [[Brain-Computer Interface (BCI)]]
- [[Brain-Derived Neurotrophic Factor (BDNF)]]
- [[Brand Consistency in AI Image Generation]]
- [[C4 Model (Architecture Documentation)]]
- [[CAP Theorem & PACELC]]
- [[Case Interviews (Consulting)]]
- [[Case Study: Allbirds PWA Redesign]]
- [[Catastrophic Forgetting & Continual Learning]]
- [[Causal Inference]]
- [[CFG Scale]]
- [[CFG Scale (Classifier-Free Guidance)]]
- [[ChatGPT / Image AI Emoticon Prompt Engineering]]
- [[ChatGPT Integration (DALL-E + LLM Pipeline)]]
- [[ChatGPT 통합 기반 텍스트 투 이미지 (Text-to-Image)]]
- [[Chrome DevTools]]
- [[Chrome DevTools Memory Profiling]]
- [[Chronic Pain Management Protocols]]
- [[CI/CD Pipeline & IDE Security Integration]]
- [[Circuit Discovery (Mechanistic Interpretability)]]
- [[Clean Code Principles]]
- [[Client-Server Architecture Pattern]]
- [[CLIP (Contrastive Language-Image Pre-training)]]
- [[Code Smells]]
- [[Codebase Maps and Interactive Tours]]
- [[Codebase Onboarding Guide]]
- [[CodeScene (Behavioral Code Analysis)]]
- [[Cognition · Overcoming · Action (인지 · 극복 · 행동)]]
- [[Cognitive Architecture]]
- [[Cognitive Biases]]
- [[Cognitive Computing]]
- [[Cognitive Constraints (Conway's Law & Cognitive Load)]]
- [[Cognitive Evaluation Theory (Self-Determination)]]
- [[Cognitive Reserve Theory]]
- [[Cognitive Therapy in CBT]]
- [[Cognitive Training Software (Aim Lab, KovaaK's)]]
- [[Collaborative Filtering]]
- [[Collaborative Programming (Pair & Mob)]]
- [[Collective Intelligence]]
- [[Combat Controls Update (War Commander, Feb 2014)]]
- [[Combat System & Bullet Interaction Pipeline]]
- [[Combined Arms (제병협동) 전술]]
- [[Commercial AI Art Production]]
- [[CompCert (Verified C Compiler)]]
- [[Computational Creativity]]
- [[Computational Linguistics]]
- [[Computational Neuroscience & Reinforcement Learning]]
- [[Compute Shader (WebGPU)]]
- [[Computer Vision]]
- [[Computer Vision Synthesis (Synthetic Data)]]
- [[Concept Drift]]
- [[Connect AI Architecture]]
- [[Connect AI Documentation]]
- [[ConnectAI Core Optimization Plan]]
- [[ConnectAI Dev Log 20260429]]
- [[Constraint Satisfaction Problems (CSP)]]
- [[Core Web Vitals]]
- [[Core Web Vitals Metrics]]
- [[Core Web Vitals Optimization (INP, LCP, CLS)]]
- [[Corgea (AI-Native SAST)]]
- [[Corporate LMS Training]]
- [[Cost-Benefit Analysis in AI]]
- [[CPTED (Crime Prevention Through Environmental Design)]]
- [[Credit Assignment Problem]]
- [[Critical Rendering Path (CRP)]]
- [[Cross-Entropy Loss]]
- [[CSS Animations & Performance]]
- [[CSS Container Queries]]
- [[Custom ESLint Rules Development]]
- [[Cybernetics Foundations]]
- [[Damage Types (Game Design)]]
- [[Data Augmentation Strategies]]
- [[Data Cleaning Algorithms]]
- [[Data Distillation]]
- [[Data Ethics and Privacy]]
- [[Data Flywheel Effect]]
- [[Data Pipeline Orchestration]]
- [[DCGAN (Deep Convolutional GAN)]]
- [[Debugging Methods]]
- [[Decision Trees and Random Forests]]
- [[Deep Grammar]]
- [[DeepCode AI (Snyk Code)]]
- [[Deepfake Technology]]
- [[Default Mode Network (DMN)]]
- [[Defensive Architecture (Game Design)]]
- [[Degrees of Freedom (DOF)]]
- [[Deliberate Practice]]
- [[Denavit-Hartenberg Parameters]]
- [[Dependency Injection (DI)]]
- [[Depth Pre-Pass]]
- [[Development Communication Standards]]
- [[DevSecOps]]
- [[Diagrams as Code]]
- [[Differentiable Programming]]
- [[Dimensionality Reduction]]
- [[Discriminated Unions]]
- [[Distributed Systems]]
- [[DOM vs Virtual DOM]]
- [[Domain-Specific Languages (DSL)]]
- [[DPO (Direct Preference Optimization)]]
- [[Drama Management Systems]]
- [[DRY Principle (Don't Repeat Yourself)]]
- [[Dynamic Creative Optimization (DCO)]]
- [[Dynamic Difficulty Adjustment (DDA)]]
- [[Dynamic Environment Handling]]
- [[Dynamic Few-Shot Selection]]
- [[Dynamic Pricing & Offers]]
- [[E-commerce Optimization]]
- [[Ecology and Ecosystem Modeling]]
- [[Economics of Information]]
- [[Edge AI and Computing]]
- [[Eligibility Traces]]
- [[Elite Sport Science Protocols]]
- [[Embodied AI]]
- [[Embodied Cognition]]
- [[Emergence in Complex Systems]]
- [[Emotional AI (Affective Computing)]]
- [[Emotionally Intelligent Tutoring Systems (EITS)]]
- [[Encapsulation and Information Hiding]]
- [[Encapsulation of Domain Invariants]]
- [[Ensemble Methods]]
- [[Enterprise Software Engineering]]
- [[Epidemiological Modeling]]
- [[Epistemic Uncertainty]]
- [[Epistemology]]
- [[ESLint Static Analysis]]
- [[Ethics & AI]]
- [[Eudaimonia and Well-being]]
- [[Eugen Systems 모딩 매뉴얼]]
- [[Event Sourcing Pattern]]
- [[Event-Driven Architecture]]
- [[Evolutionary Biology]]
- [[Excessive Agency (LLM)]]
- [[Execution Environment (Sandbox)]]
- [[Executive Function Deficit]]
- [[Exhaustiveness Checking]]
- [[Experience Replay]]
- [[Explainable AI (XAI)]]
- [[Exploding Gradient Problem]]
- [[Exploratory Data Analysis (EDA)]]
- [[Expo 2025 Osaka]]
- [[Exponential Growth]]
- [[Extended Reality (XR)]]
- [[Extreme Programming (XP)]]
- [[Factor Analysis]]
- [[Factory Pattern]]
- [[Failable Task Handling]]
- [[Fate War]]
- [[Feature Clamping (피처 고정)]]
- [[Feature Engineering]]
- [[Figma Integration]]
- [[Figurative Language]]
- [[Fine-tuning]]
- [[Finished Goods (제품 완성품)]]
- [[Finite Element Analysis (FEA)]]
- [[Finite State Machines (FSM)]]
- [[Fitness Landscape]]
- [[Flash Attention]]
- [[Flexbox]]
- [[Focal Loss]]
- [[Formal Methods]]
- [[Foundation Models]]
- [[Frame Type Restoration]]
- [[Free Energy Principle (FEP)]]
- [[Fuzzy Logic]]
- [[G-Stack Principles]]
- [[Game System Design Prompt]]
- [[Gaussian Processes (GP)]]
- [[Generalization in AI]]
- [[Generative Adversarial Networks (GAN)]]
- [[Generative AI]]
- [[Geriatric Medicine]]
- [[Git Branching Strategies]]
- [[Global Standard]]
- [[Goal-Oriented Action Planning (GOAP)]]
- [[Google Page Experience 2025 Update]]
- [[GPU]]
- [[GPU Acceleration (Compositing)]]
- [[GPU Programming with CUDA]]
- [[Graph Neural Networks (GNN)]]
- [[Grit]]
- [[Grouped-Query Attention (GQA)]]
- [[Growth Mindset]]
- [[GRPO (Group Relative Policy Optimization)]]
- [[Hallucination in LLMs]]
- [[Heuristics]]
- [[Hexagonal Architecture]]
- [[Hidden Markov Model (HMM)]]
- [[High Availability Systems]]
- [[Homeostasis (항상성)]]
- [[Homomorphic Encryption (HE)]]
- [[Hopfield Network]]
- [[Human-Centered AI (HCAI)]]
- [[Human-in-the-Loop (HITL)]]
- [[Hyperparameters]]
- [[ICRE Framework]]
- [[IEEE P3652.1 (Federated ML Standard)]]
- [[Ikigai (이키가이)]]
- [[Image Classification]]
- [[Image Parameters]]
- [[Image Prompt 작성 방법]]
- [[Image Segmentation]]
- [[Imbalanced Data Handling]]
- [[Independent Component Analysis (ICA)]]
- [[Inductive Bias]]
- [[Information Retrieval (IR)]]
- [[Information Theory]]
- [[Innovative Problem Solving]]
- [[InstancedMesh2 library]]
- [[Integrated Development Environment]]
- [[Intellectual Property in AI]]
- [[Intentional Failure Induction]]
- [[Interaction to Next Paint (INP)]]
- [[Interdisciplinary Research]]
- [[Interop 2026]]
- [[Introduction to Programming]]
- [[Introspection (자기성찰)]]
- [[Inverse Kinematics (IK)]]
- [[IoT and AI Integration]]
- [[Isaac Asimov's Laws of Robotics]]
- [[Iterative Prompting]]
- [[JIT Compilation in AI Engines]]
- [[JSON-LD Structured Data]]
- [[Just-in-time Data Loading]]
- [[K-Means Clustering]]
- [[K-Nearest Neighbors (k-NN)]]
- [[Kernel Methods and SVMs]]
- [[Key-Value (KV) Cache]]
- [[Knowledge Representation in AI]]
- [[L1 and L2 Regularization]]
- [[Label Noise and Robustness]]
- [[Large Frontend Projects]]
- [[Latent Dirichlet Allocation]]
- [[Latent Semantic Analysis (LSA)]]
- [[Layer Normalization]]
- [[Layout Thrashing]]
- [[Lazy Loading Strategies]]
- [[Leaky ReLU and Activations]]
- [[Lean Operations]]
- [[Legacy Modernization]]
- [[Lifecycle Hooks]]
- [[Lighting and Composition]]
- [[Linear Discriminant Analysis]]
- [[Linear Programming]]
- [[Linear Regression Mastery]]
- [[Linguistic Analysis in AI]]
- [[LLM Ops and Tuning]]
- [[LLM-as-a-Judge (LaaJ)]]
- [[LLM-based Code Analysis]]
- [[Load Balancing Strategies]]
- [[Local AI and Infrastructure]]
- [[Local Brain Management]]
- [[LOD]]
- [[Logic]]
- [[Logistic Regression Foundations]]
- [[Long Animation Frames API]]
- [[Long Tail]]
- [[Long Tasks API]]
- [[Loss Functions Foundations]]
- [[Machine Zone의 4X 포트폴리오 확장 및 라이브 서비스 모델 고도화]]
- [[Macros (매크로)]]
- [[Main Thread]]
- [[Manhattan Distance]]
- [[MAP Estimation (Maximum A Posteriori)]]
- [[Markov Chain Monte Carlo (MCMC)]]
- [[Markov Chains]]
- [[Matrix Factorization]]
- [[Matrix Operations and AI]]
- [[Mean Absolute Error (MAE)]]
- [[Mean Squared Error (MSE)]]
- [[Mechanistic Interpretability (기계적 해석 가능성)]]
- [[Medical Imaging Data Augmentation]]
- [[Memory Hierarchy]]
- [[Mermaid Diagrams as Code]]
- [[Micro-management (RTS)]]
- [[Midjourney]]
- [[Mipmap]]
- [[Miscellaneous AI Topics]]
- [[Mixed Platoons (혼합 편대)]]
- [[Mixture of Experts (MoE) & Sparse Architectures]]
- [[Mobile AI Optimization]]
- [[Mobile-First Approach]]
- [[Model Parameters]]
- [[Modern Engineering Practices (현대적 엔지니어링 프랙티스)]]
- [[Modern Scalable Frontend Architecture]]
- [[Momentum and Optimization]]
- [[Monetization (BM)]]
- [[Monopoly GO! 및 Royal Match의 라이브 이벤트 구조]]
- [[Monte Carlo Methods]]
- [[Moodboard Creation]]
- [[Morphological and Syntactic Analysis]]
- [[Multi-armed Bandit Problem]]
- [[Multinomial Naive Bayes]]
- [[Naive Bayes Classifiers]]
- [[Named Entity Recognition (NER)]]
- [[Natural Language Generation (NLG)]]
- [[Natural Language Processing (NLP)]]
- [[Negative Prompt]]
- [[Neural Architecture Search (NAS)]]
- [[Neural Darwinism]]
- [[Neural Style Transfer]]
- [[Neural-Symbolic Integration]]
- [[Neurodevelopmental Disorders]]
- [[Neuropharmacology of Substance Use Disorders]]
- [[Neuroprosthetics Development]]
- [[Neuropsychiatric Disorders]]
- [[Neurorehabilitation Post-Stroke]]
- [[NLP Attention Mechanisms]]
- [[No Man's Sky]]
- [[Noise Reduction in AI]]
- [[Non-parametric Models]]
- [[Normalization]]
- [[NotebookLM Research Workflow]]
- [[Object Detection Foundations]]
- [[Occupational Therapy]]
- [[Olympic Training Protocols]]
- [[Omni Reference (--oref)]]
- [[On-Device AI (Mobile / Gemma)]]
- [[One-Hot Encoding]]
- [[Ontology Engineering]]
- [[Open Source AI Ecosystem]]
- [[OpenAI API Integration]]
- [[Operation - Western Sun]]
- [[Optical Character Recognition]]
- [[Optimization in AI]]
- [[Ordinal Data Analysis]]
- [[Out-of-Distribution Detection]]
- [[Outlier Detection Techniques]]
- [[P-Reinforce]]
- [[P-Reinforce 위키 포맷 정본]]
- [[Parameter]]
- [[Parameter Control]]
- [[Parameter Sharing]]
- [[Pareto Principle]]
- [[Pattern Recognition]]
- [[PEFT (Parameter-Efficient Fine-Tuning)]]
- [[Perceptrons-Foundations]]
- [[Philosophy]]
- [[Physical Intelligence]]
- [[Physics-informed Neural Networks]]
- [[Plutchik's Wheel of Emotions]]
- [[PMI Technique (Pointwise Mutual Information)]]
- [[Poetic Computation]]
- [[Point Cloud Processing]]
- [[Point of Sale]]
- [[Policy Optimization]]
- [[POMDP]]
- [[Pooling]]
- [[Pose Estimation]]
- [[Positive Prompt]]
- [[Positive Reinforcement]]
- [[Pre-processing Data for AI]]
- [[Precision-Recall Tradeoff]]
- [[Predictive Analytics]]
- [[Predictive Coding]]
- [[Predictive Maintenance]]
- [[Prenatal Neurology]]
- [[Principal Component Analysis]]
- [[Privacy Preserving AI]]
- [[Probability and Logic Fusion]]
- [[Problem Solving Test (PST)]]
- [[Procedural Narrative Generation]]
- [[Process Automation with AI]]
- [[Processing]]
- [[Productivity Hacks for Devs]]
- [[Prompt Weight]]
- [[Proprioception]]
- [[Pros Cons Table]]
- [[Pull Request (PR)]]
- [[PyTorch Foundations]]
- [[PyTorch Lightning]]
- [[Quality Gates]]
- [[Quantum Computing for AI]]
- [[Real-time Operation]]
- [[Recommendation Systems]]
- [[Reconciliation]]
- [[Refactoring Best Practices]]
- [[Reference]]
- [[Refinement]]
- [[Reflection]]
- [[Reflow and Repaint]]
- [[Render Tree]]
- [[Replenishment]]
- [[Requirements]]
- [[Reranking]]
- [[Research]]
- [[ResNet Architectures]]
- [[Reward Prediction Error]]
- [[Reward Shaping in RL]]
- [[Ring Attention]]
- [[Rise of Kingdoms]]
- [[Risk Assessment with AI]]
- [[RL Neuroscience]]
- [[Robotics]]
- [[Robustness]]
- [[ROC-AUC Curves]]
- [[ROUGE Metrics]]
- [[Rule-based Systems]]
- [[SaaS (Software as a Service)]]
- [[Samuel Beckett]]
- [[SAR (Synthetic Aperture Radar)]]
- [[SARD 안티치트 솔루션 (SARD Anti-Cheat)]]
- [[SCA Fundamentals (Software Composition Analysis)]]
- [[SCADA]]
- [[Scalability in AI Systems]]
- [[Scaling Laws for LLMs]]
- [[Schema]]
- [[Science of Failure]]
- [[Scientific Communication]]
- [[SCM (Supply Chain Management)]]
- [[Search Methodology]]
- [[Search Optimization]]
- [[Secrets Detection]]
- [[Sector Breach August 2025]]
- [[Secure Multi-party Computation]]
- [[Seed]]
- [[Segments.ai]]
- [[Selective State Space Models (Mamba)]]
- [[Self-Driving Car Foundations]]
- [[Self-Evolving Agent 기법 조사 (2026-06)]]
- [[Self-Play (자기 대결 기반 강화학습)]]
- [[Self-Verification]]
- [[Semantic Grounding & Provenance]]
- [[Semantic Search]]
- [[Semgrep Assistant]]
- [[Sensitivity Analysis]]
- [[Sentiment Analysis]]
- [[Separation of Concerns (관심사의 분리)]]
- [[Sequence Diagram]]
- [[Sequence to Sequence Models]]
- [[Serverless Computing for AI]]
- [[shadcn/ui]]
- [[Shape Feature Extraction]]
- [[Similarity Metrics in AI]]
- [[Simulation Environments]]
- [[Skybound Asset Generation Roadmap]]
- [[Skybound Defensive Architecture Reboot]]
- [[Skybound Firepower Overclock v1.5]]
- [[Skybound Protocol 코드리뷰]]
- [[Smart Contract Auditing]]
- [[SME (Subject Matter Expert / Small-Medium Enterprise)]]
- [[Snyk Checkmarx Endor Labs 등 종합 애플리케이션 보안 플랫폼]]
- [[Soft Navigation]]
- [[Software Architecture Pattern]]
- [[Software Architecture Styles]]
- [[Software Composition Analysis (SCA)]]
- [[Software Maintenance]]
- [[Solution]]
- [[SonarQube]]
- [[Sparse Attention]]
- [[Sparse Data Handling]]
- [[Spatial Partitioning]]
- [[Spectral Clustering]]
- [[Speech Recognition Foundations]]
- [[Speech Synthesis]]
- [[Spiking Neural Networks (SNNs)]]
- [[Splash Damage]]
- [[SPOF (Single Point of Failure)]]
- [[SSQ Questionnaire]]
- [[Stages of Grief]]
- [[Staircase Monetization Model]]
- [[Startup]]
- [[Startup Projects]]
- [[State Space]]
- [[Static Site Generation (SSG)]]
- [[Stem Analysis]]
- [[Straightening]]
- [[Structuralism]]
- [[Structurizr]]
- [[Style Reference (--sref)]]
- [[Style Transfer]]
- [[StyleCounsel]]
- [[Styletron]]
- [[Superficiality Metrics]]
- [[Supply Chain]]
- [[Support Insulated]]
- [[Sustainability]]
- [[Symbolic AI vs Connectionism]]
- [[Symbols]]
- [[Symmetry and Invariance]]
- [[Synergy]]
- [[Synthesized Intelligence]]
- [[Synthetic Data]]
- [[System Prompt (시스템 프롬프트)]]
- [[System Theory]]
- [[Tactical Air Drop and Supply Logistics]]
- [[Tactical Evolution of the War Commander Combat Ecosystem]]
- [[Tailwind CSS v4]]
- [[Team Collaboration]]
- [[Team Topologies]]
- [[TensorFlow Foundations]]
- [[Term Frequency-Inverse Document Frequency]]
- [[Test Time Compute Scaling (추론 시간 계산 스케일링)]]
- [[Test-Driven Development]]
- [[Text Mining]]
- [[The Evolution of Music Distribution]]
- [[Theory of Constraints (TOC)]]
- [[Theory of Mind (ToM) in AI]]
- [[Threejs WebGPURenderer]]
- [[Time Series Analysis]]
- [[Time to Interactive (TTI)]]
- [[Tokenization & Subword Processing]]
- [[Tool Usage Optimization]]
- [[Toxicity and Bias Mitigation]]
- [[Trustworthy AI]]
- [[Turing Test]]
- [[Ubiquitous Language]]
- [[Ultra Efficiency]]
- [[Unconscious Structuralism]]
- [[Unit Stances]]
- [[Universal Approximation Theorem]]
- [[Universal Basic Income (UBI)]]
- [[useDeferredValue]]
- [[useTransition]]
- [[V-component (Evaluation Interface)]]
- [[Vary Region (인페인팅)]]
- [[Virtual DOM과 Reconciliation]]
- [[Vocabulary Expansion]]
- [[Voice Assistant Architecture]]
- [[War Commander 전투 시스템]]
- [[Weak Central Coherence]]
- [[Web3 and AI Integration]]
- [[WebSplatter (3D Gaussian Splatting)]]
- [[What is AI]]
- [[Willingness to Pay (WTP)]]
- [[Word Representation]]
- [[Work Displacement (AI 노동 대체)]]
- [[Workflow Integrity]]
- [[게이미피케이션]]
- [[공급망 공격 (Supply Chain Attack)]]
- [[구역 통제 및 동맹 전쟁 (Sector Control and Alliance Wars)]]
- [[기지 레이아웃 메타 (Base Layout Meta)]]
- [[기지 방어 (Base Defense)]]
- [[다수 팀 협업 환경]]
- [[단일 코드베이스를 통한 멀티 디바이스(모바일-데스크톱) 웹 인터페이스 구축]]
- [[데이터 기반 밸런싱 (Data-Driven Balancing)]]
- [[데이터 중심의 SaaS 어드민 패널 및 CRM 대시보드 구축]]
- [[덱 빌딩 (Deck building)]]
- [[렌더링 최적화 개념 설명 자료]]
- [[렌더링 파이프라인(Rendering Pipeline)]]
- [[맞춤형 팩 (Personalized Packs)]]
- [[모델 매개변수 제어 (Model Parameter Control)]]
- [[모듈식 컴포넌트 (Modular Components)]]
- [[미드저니 및 스테이블 디퓨전의 부분 편집 기법]]
- [[미디어 쿼리(Media Queries)]]
- [[미호요(miHoYo)]]
- [[반응형 디자인]]
- [[버전 및 모델 (Versions and Models)]]
- [[병원 (Hospital)]]
- [[부정 프롬프트와 가중치를 활용한 시각적 아티팩트(Artifact) 디버깅 및 제어]]
- [[브라우저 렌더링 프로세스 (CRP)]]
- [[브라우저 메모리 누수 탐지(Browser Memory Leak Detection)]]
- [[브라우저 메인 스레드 최적화 및 타임 슬라이싱]]
- [[사후 편집 (Post-editing)]]
- [[상성 및 데미지 유형(Unit Counters & Damage Profiles)]]
- [[상업용 브랜드 이미지 및 디자인 시스템 구축]]
- [[상업용 제품 사진 및 브랜드 로고 디자인]]
- [[상태 관리 및 API 응답 모델링 (State Management and API Response Modeling)]]
- [[상태 관리 최적화 (Zustand Jotai Valtio)]]
- [[샘플링 스텝 (Sampling Steps)]]
- [[성능 중심의 웹 애니메이션 및 인터랙션 구현]]
- [[세계 지도(World Map)]]
- [[섹터 분쟁 및 전초기지 전투(Sector Warfare and Elite Event Operations)]]
- [[소셜 미디어 그래픽 및 마케팅 캠페인 제작]]
- [[소프트웨어 아키텍처 다이어그램 (Software Architecture Diagrams)]]
- [[숨겨진 스탯 (Hidden Stats)]]
- [[스타일 코드 (Style Codes)]]
- [[스테이블 디퓨전 기반 정밀 이미지 합성 및 해부학적 오류 수정 파이프라인]]
- [[스테이블 디퓨전의 가중치 및 제어 시스템]]
- [[시리즈물 및 다중 샷 워크플로우 (Series and Multi-shot Workflow)]]
- [[안구 운동 증상(Oculomotor Symptoms)]]
- [[애니메이션 (transition / keyframes)]]
- [[약탈적 수익화 (Predatory Monetization)]]
- [[에셋 재사용(Asset Reuse)]]
- [[오픈소스 기반 맞춤형 이미지 생성 워크플로우 구축]]
- [[오픈소스 이미지 모델 미세 조정 및 배포]]
- [[오픈소스 컴포넌트 (Open Source Components)]]
- [[원신(Genshin Impact)]]
- [[월드 오브 워크래프트(World of Warcraft)]]
- [[웹 접근성 및 prefers-reduced-motion]]
- [[웹 접근성 및 성능 최적화]]
- [[유닛 상성(Unit Counters)]]
- [[유지보수 가능한 CSS 아키텍처(CSS Modules & Tailwind)]]
- [[유지보수성(Maintainability)]]
- [[유틸리티 퍼스트(Utility-first)]]
- [[이미지 생성 및 제어 파이프라인]]
- [[이미지 생성 최적화 (Image Generation Optimization)]]
- [[인-이미지 텍스트(In-Image Text)]]
- [[인공지능 시각 언어 생성 (AI Visual Language Generation)]]
- [[일관된 캐릭터 및 스타일 구축]]
- [[자연어 아티팩트 (Natural Language Artifacts)]]
- [[자연어 프롬프트(Natural Language Prompt)]]
- [[전자상거래 소비자 참여 및 보상 시스템 최적화]]
- [[전자상거래 플랫폼]]
- [[전투 전술(Battle Strategies)]]
- [[정적 분석 툴 (ESLint, Prettier)]]
- [[제로잉 (Getting Zero-ed)]]
- [[제병협동 (Combined Arms)]]
- [[조명 및 카메라 사양 지시(Lighting and Camera Specification)]]
- [[초기 로드 시간 (Initial Load Time)]]
- [[초상화 및 애니메이션 스타일 제어]]
- [[초인플레이션(Hyperinflation)]]
- [[카산드라(Cassandra)]]
- [[코드 속성 그래프 CPG]]
- [[코드베이스 읽기 지식]]
- [[크로스 플랫폼 기술(Cross-Platform Technology)]]
- [[텍스트 렌더링(Text Rendering)]]
- [[페이 투 윈 (Pay to Win)]]
- [[포탑 시스템(Turret Systems)]]
- [[프론트엔드 기초 구조 이해]]
- [[프론트엔드 기초 구조 이해 핵심 목적]]
- [[프롬프트 구문 (Prompt Syntax)]]
- [[플랫폼 저항성(Platform Resistances)]]
- [[하이브리드 코드 리뷰]]
- [[해부학적 오류 디버깅 워크플로우]]
- [[확장 가능한 스타일 시스템]]
@@ -0,0 +1,37 @@
---
id: rlhf
title: "RLHF"
category: "AI"
status: "draft"
verification_status: "conceptual"
canonical_id: ""
aliases: ["RLHF", "Reinforcement Learning from Human Feedback", "인간 피드백 강화학습"]
duplicate_of: ""
source_trust_level: "B"
confidence_score: 0.80
created_at: 2026-07-11
updated_at: 2026-07-11
review_reason: "깨진 링크 다발 해소용 AI 생성 초안 — 원출처 리서치로 검증·보강 권장"
merge_history: []
tags: ["ai","llm","training"]
raw_sources: []
applied_in: []
github_commit: ""
---
# [[RLHF]]
## 🎯 한 줄 통찰 (One-line insight)
인간의 선호 판단을 보상 신호로 바꿔 언어 모델을 미세조정하는 기법 — "정답"을 정의하기 어려운 품질(유용함·무해함)을 사람의 비교 선택으로 학습시킨다.
## 🧠 핵심 개념 (Core concepts)
- **3단계 파이프라인** — ① 지시 데이터로 SFT(지도 미세조정) ② 사람이 응답 쌍을 비교한 데이터로 보상 모델 학습 ③ 보상 모델을 신호로 정책(LLM)을 강화학습(PPO 등) 최적화.
- **보상 해킹 위험** — 모델이 보상 모델의 허점을 파고들어 점수만 높은 응답을 낸다. KL 페널티로 원 모델에서 과도하게 벗어나지 않게 잡는다.
- **변형들** — 보상 모델 없이 선호 쌍으로 직접 최적화하는 DPO 등 경량 대안이 실무에서 확산됐다.
- **아첨(sycophancy) 부작용** — 사람이 "듣기 좋은 답"을 선호하는 경향이 보상에 새어들어 모델이 아부하게 될 수 있다.
## 🧩 추출된 패턴 (Extracted patterns)
- RLHF 의 품질은 알고리즘보다 선호 데이터의 품질(누가·어떤 기준으로 비교했나)이 결정한다.
## 🔗 Knowledge Connections
- **Related Topics:** [[Software Architecture]]