AI 人工智能包含的领域方向

学无止境，人工智能领域所包含的所有方向如下：

Agent-based and Multi-agent Systems	Multidisciplinary Topics and Applications
Agent Communication	AI Hardware
Agent Societies	Arts and Creativity
Agent Theories and Models	Bioinformatics
Agent-Based Simulation and Emergence	Computational Sustainability
Agreement Technologies: Argumentation	Computer Games
Agreement Technologies: Negotiation and Contract-Based Systems	Databases
Algorithmic Game Theory	Economics
Applications	Education
Computational Social Choice	Finance
Cooperative Games	Game Playing
Coordination and Cooperation	Health and Medicine
Economic Paradigms, Auctions and Market-Based Systems	Humanities
Engineering Methods, Platforms, Languages and Tools	Interactive Entertainment
Formal Verification, Validation and Synthesis	Life Science
Human-Agent Interaction	News and Media
Mechanism Design	Other
Multi-agent Learning	Physical Science
Multi-agent Planning	Real-Time Systems
Noncooperative Games	Security and Privacy
Normative systems	Smart Cities
Other	Social Sciences
Resource Allocation	Software Engineering
Trust and Reputation	Sports
AI Ethics, Trust, Fairness	Sustainable Development Goals
Accountability	Transportation
AI and Law, Governance, Regulation	Ubiquitous Computing Systems
Bias	Validation and Verification
Ethical, Legal and Societal Issues	Web and Social Networks
Explainability and Interpretability	Natural Language Processing
Fairness & Diversity	Applications
Moral Decision Making	Coreference Resolution
Other	Dialogue and Interactive Systems
Robot Rights	Embeddings
Safety & Robustness	Information Extraction
Societal Impact of AI	Information Retrieval and Text Mining
Trustworthy AI	Interpretability and Analysis of Models for NLP
Values	Knowledge Extraction
Computer Vision	Language Generation
3D Computer Vision	Language Grounding
Action and Behaviour Recognition	Language Models
Adversarial learning, adversarial attack and defense methods	Machine Translation and Multilinguality
Applications	Named Entities
Bias, Fairness & Privacy	Natural Language Semantics
Biomedical Image Analysis	Other
Biometrics, Face, Gesture and Pose Recognition	Phonology, Morphology, and Word Segmentation
Computational photography	Psycholinguistics
Image and Video retrieval	Question Answering
Interpretability and Transparency	Resources and Evaluation
Machine Learning for Vision	Sentiment Analysis and Text Mining
Motion and Tracking	Speech
Neural generative models, auto encoders, GANs	Summarization
Other	Tagging, Chunking, and Parsing
Recognition (object detection, categorization)	Text Classification
Representation Learning	Tools
Scene analysis and understanding	Planning and Scheduling
Segmentation	Activity and Plan Recognition
Structural and Model-Based Approaches, Knowledge Representation and Reasoning	Applications
Transfer, low-shot, semi- and un- supervised learning	Distributed; Multi-agent Planning
Video analysis and understanding	Hierarchical Planning
Vision and language	Learning in Planning and Scheduling
Visual reasoning and symbolic representation	Markov Decisions Processes
Constraint Satisfaction and Optimization	Mixed Discrete/Continuous Planning
Applications	Model-Based Reasoning
Constraint Optimization	Planning Algorithms
Constraint Programming	Planning under Uncertainty
Constraint Satisfaction	Planning with Incomplete Information
Constraints and Machine Learning	POMDPs
Distributed Constraints	Real-time Planning
Mixed Discrete and Continuous	Robot Planning
Modeling	Routing
Other	Scheduling
Satisfiabilty	Search in Planning and Scheduling
Solvers and Tools	Theoretical Foundations of Planning
Data Mining	Robotics
Anomaly/Outlier Detection	Applications
Applications	Behavior and Control
Big Data and Scalability	Cognitive Robotics
Class Imbalance and Unequal Cost	Human Robot Interaction
Collaborative Filtering	Learning in Robotics
Data Visualisation	Localization, Mapping, State Estimatino
Exploratory Data Mining	Manipulation
Federated Learning	Motion and Path Planning
Frequent Pattern Mining	Multi-Robot Systems
Information Retrieval	Other
Intelligent Database Systems	Perception
Knowledge Graphs and Knowledge Base Completion	Robotics and Vision
Mining Codebase and Software Repository	Search
Mining Data Streams	Algorithm portfolios and configuration
Mining Graphs	Applications
Mining Heterogenous Data	Combinatorial Search and Optimisation
Mining Semi Structured Data	Distributed Search
Mining Spatial and/or Temporal Data	Evolutionary Computation
Mining Text, Web, Social Media	Game Playing
Networks	Heuristic Search
Other	Local search
Parallel, Distributed and Cloud-based High Performance Mining	Meta-Reasoning and Meta-Heuristics
Privacy Preserving Data Mining	Mixed Discrete/Continuous Search
Recommender Systems	Other
Theoretical Foundations of Data Mining	Search and Machine Learning
Humans and AI	Uncertainty in AI
Applications	Applications
Brain Sciences	Bayesian Networks
Cognitive Modeling	Causality, Structural Causal Models and Causal Inference
Cognitive Systems	Decision and Utility Theory
Computational Sustainability and Human Well-Being	Graphical Models
Computer-Aided Education	Inference
Human Computation and Crowdsourcing	Nonprobabilistic Models
Human-AI Collaboration	Other
Human-Computer Interaction	Probabilistic Programming
Intelligent User Interfaces	Sequential Decision Making
Other	Statistical Relational AI
Personalization and User Modeling	Tractable Probabilistic Models
Knowledge Representation and Reasoning	Uncertainty Representations
Applications
Argumentation
Automated Reasoning and Theorem Proving
Belief Change
Case-based Reasoning
Causality
Common-Sense Reasoning
Computational Complexity of Reasoning
Description Logics and Ontologies
Diagnosis and Abductive Reasoning
Knowledge Compilation and Tractable Languages
Knowledge Representation Languages
Learning and reasoning
Logic Programming
Non-monotonic Reasoning
Other
Preference Modelling and Preference-Based Reasoning
Qualitative, Geometric, Spatial, Temporal Reasoning
Reasoning about actions
Reasoning about Knowledge and Belief
Semantic Web
Machine Learning
Active Learning
Adversarial Machine Learning
Applications
Attention Models
Autoencoders
Automated Machine Learning
Bayesian Learning
Causality
Classification
Clustering
Convolutional Networks
Cost-Sensitive Learning
Deep Reinforcement Learning
Ensemble Methods
Evaluation
Evolutionary Learning
Experimental Methodology
Explainable/Interpretable Machine Learning
Feature Extraction, Selection and Dimensionality Reduction
Federated Learning
Few-shot learning
Generative Adverserial Networks
Geometric Learning
Hyperparameter Optimization
Incremental Learning
Kernel Methods
Knowledge Aided Learning
Learning Graphical Models
Learning Preferences or Rankings
Learning Sparse Models
Learning Theory
Meta-Learning
Multi-instance
Multi-label
Multi-modal learning
Multi-task and Transfer Learning
Multi-view learning
Neuro-Symbolic Methods
Online Learning
Optimisation
Other
Probabilistic Machine Learning
Recommender Systems
Recurrent Networks
Regression
Reinforcement Learning
Relational Learning
Representation learning
Robustness
Self-supervised Learning
Semi-Supervised Learning
Sequence and Graph Learning
Structured Prediction
Symbolic methods
Theory of Deep Learning
Time-series; Data Streams
Unsupervised Learning
Weakly Supervised Learning

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