Mathematics Branches, Topics, and Sub-Topics

A structured visual guide to the major mathematical areas and their relationships.

Search by code, branch, topic, subtopic, or a keyword from the descriptions.

68Txx Artificial intelligence

This subtopic introduces the core ideas in artificial intelligence, including foundational concepts, standard methods, and the main questions used to organize the area. Typical uses include building mathematical background, framing related research problems, and supporting applications in neighboring fields where these concepts provide useful structure.

Specific topics

68T01 General topics in artificial intelligence

Overview

This topic examines general topics in artificial intelligence within artificial intelligence and machine learning methods, focusing on the main concepts, representational choices, and standard questions used in modern research and practice. It provides a concise starting point for understanding how the topic fits into the wider field.

Related Wikipedia Page

Artificial intelligence (Wikipedia)

Useful Links

Key Ideas

  • Representation of knowledge and uncertainty
  • Learning from data with statistical and symbolic methods
  • Planning and decision-making under constraints

Typical Uses

Used to design intelligent systems that perceive, learn, reason, and act on information.

Applications

  • Classification and prediction
  • Robotics and planning
  • Natural language and search systems

References

Recommended Textbooks

68T05 Learning and adaptive systems in artificial intelligence

Overview

This topic examines learning and adaptive systems in artificial intelligence within artificial intelligence and machine learning methods, focusing on the main concepts, representational choices, and standard questions used in modern research and practice. It provides a concise starting point for understanding how the topic fits into the wider field.

Related Wikipedia Page

Artificial intelligence (Wikipedia)

Useful Links

Key Ideas

  • Representation of knowledge and uncertainty
  • Learning from data with statistical and symbolic methods
  • Planning and decision-making under constraints

Typical Uses

Used to design intelligent systems that perceive, learn, reason, and act on information.

Applications

  • Classification and prediction
  • Robotics and planning
  • Natural language and search systems

References

Recommended Textbooks

68T07 Artificial neural networks and deep learning

Overview

This topic examines artificial neural networks and deep learning within artificial intelligence and machine learning methods, focusing on the main concepts, representational choices, and standard questions used in modern research and practice. It provides a concise starting point for understanding how the topic fits into the wider field.

Related Wikipedia Page

Artificial intelligence (Wikipedia)

Useful Links

Key Ideas

  • Representation of knowledge and uncertainty
  • Learning from data with statistical and symbolic methods
  • Planning and decision-making under constraints

Typical Uses

Used to design intelligent systems that perceive, learn, reason, and act on information.

Applications

  • Classification and prediction
  • Robotics and planning
  • Natural language and search systems

References

Recommended Textbooks

68T09 Computational aspects of data analysis and big data

Overview

This topic examines computational aspects of data analysis and big data within artificial intelligence and machine learning methods, focusing on the main concepts, representational choices, and standard questions used in modern research and practice. It provides a concise starting point for understanding how the topic fits into the wider field.

Related Wikipedia Page

Artificial intelligence (Wikipedia)

Useful Links

Key Ideas

  • Representation of knowledge and uncertainty
  • Learning from data with statistical and symbolic methods
  • Planning and decision-making under constraints

Typical Uses

Used to design intelligent systems that perceive, learn, reason, and act on information.

Applications

  • Classification and prediction
  • Robotics and planning
  • Natural language and search systems

References

Recommended Textbooks

68T10 Pattern recognition, speech recognition

Overview

This topic examines pattern recognition, speech recognition within artificial intelligence and machine learning methods, focusing on the main concepts, representational choices, and standard questions used in modern research and practice. It provides a concise starting point for understanding how the topic fits into the wider field.

Related Wikipedia Page

Artificial intelligence (Wikipedia)

Useful Links

Key Ideas

  • Representation of knowledge and uncertainty
  • Learning from data with statistical and symbolic methods
  • Planning and decision-making under constraints

Typical Uses

Used to design intelligent systems that perceive, learn, reason, and act on information.

Applications

  • Classification and prediction
  • Robotics and planning
  • Natural language and search systems

References

Recommended Textbooks

68T15 Theorem proving (deduction, resolution, etc.)

Overview

This topic examines theorem proving (deduction, resolution, etc.) within artificial intelligence and machine learning methods, focusing on the main concepts, representational choices, and standard questions used in modern research and practice. It provides a concise starting point for understanding how the topic fits into the wider field.

Related Wikipedia Page

Artificial intelligence (Wikipedia)

Useful Links

Key Ideas

  • Representation of knowledge and uncertainty
  • Learning from data with statistical and symbolic methods
  • Planning and decision-making under constraints

Typical Uses

Used to design intelligent systems that perceive, learn, reason, and act on information.

Applications

  • Classification and prediction
  • Robotics and planning
  • Natural language and search systems

References

Recommended Textbooks

68T17 Ontology-based knowledge systems

Overview

This topic examines ontology-based knowledge systems within artificial intelligence and machine learning methods, focusing on the main concepts, representational choices, and standard questions used in modern research and practice. It provides a concise starting point for understanding how the topic fits into the wider field.

Related Wikipedia Page

Artificial intelligence (Wikipedia)

Useful Links

Key Ideas

  • Representation of knowledge and uncertainty
  • Learning from data with statistical and symbolic methods
  • Planning and decision-making under constraints

Typical Uses

Used to design intelligent systems that perceive, learn, reason, and act on information.

Applications

  • Classification and prediction
  • Robotics and planning
  • Natural language and search systems

References

Recommended Textbooks

68T20 Problem solving (heuristics, search strategies, etc.)

Overview

This topic examines problem solving (heuristics, search strategies, etc.) within artificial intelligence and machine learning methods, focusing on the main concepts, representational choices, and standard questions used in modern research and practice. It provides a concise starting point for understanding how the topic fits into the wider field.

Related Wikipedia Page

Artificial intelligence (Wikipedia)

Useful Links

Key Ideas

  • Representation of knowledge and uncertainty
  • Learning from data with statistical and symbolic methods
  • Planning and decision-making under constraints

Typical Uses

Used to design intelligent systems that perceive, learn, reason, and act on information.

Applications

  • Classification and prediction
  • Robotics and planning
  • Natural language and search systems

References

Recommended Textbooks

68T27 Logic in artificial intelligence

Overview

This topic examines logic in artificial intelligence within artificial intelligence and machine learning methods, focusing on the main concepts, representational choices, and standard questions used in modern research and practice. It provides a concise starting point for understanding how the topic fits into the wider field.

Related Wikipedia Page

Artificial intelligence (Wikipedia)

Useful Links

Key Ideas

  • Representation of knowledge and uncertainty
  • Learning from data with statistical and symbolic methods
  • Planning and decision-making under constraints

Typical Uses

Used to design intelligent systems that perceive, learn, reason, and act on information.

Applications

  • Classification and prediction
  • Robotics and planning
  • Natural language and search systems

References

Recommended Textbooks

68T30 Knowledge representation

Overview

This topic examines knowledge representation within artificial intelligence and machine learning methods, focusing on the main concepts, representational choices, and standard questions used in modern research and practice. It provides a concise starting point for understanding how the topic fits into the wider field.

Related Wikipedia Page

Artificial intelligence (Wikipedia)

Useful Links

Key Ideas

  • Representation of knowledge and uncertainty
  • Learning from data with statistical and symbolic methods
  • Planning and decision-making under constraints

Typical Uses

Used to design intelligent systems that perceive, learn, reason, and act on information.

Applications

  • Classification and prediction
  • Robotics and planning
  • Natural language and search systems

References

Recommended Textbooks

68T35 Computer vision and scene understanding

Overview

This topic examines computer vision and scene understanding within artificial intelligence and machine learning methods, focusing on the main concepts, representational choices, and standard questions used in modern research and practice. It provides a concise starting point for understanding how the topic fits into the wider field.

Related Wikipedia Page

Artificial intelligence (Wikipedia)

Useful Links

Key Ideas

  • Representation of knowledge and uncertainty
  • Learning from data with statistical and symbolic methods
  • Planning and decision-making under constraints

Typical Uses

Used to design intelligent systems that perceive, learn, reason, and act on information.

Applications

  • Classification and prediction
  • Robotics and planning
  • Natural language and search systems

References

Recommended Textbooks

68T37 Reasoning under uncertainty

Overview

This topic examines reasoning under uncertainty within artificial intelligence and machine learning methods, focusing on the main concepts, representational choices, and standard questions used in modern research and practice. It provides a concise starting point for understanding how the topic fits into the wider field.

Related Wikipedia Page

Artificial intelligence (Wikipedia)

Useful Links

Key Ideas

  • Representation of knowledge and uncertainty
  • Learning from data with statistical and symbolic methods
  • Planning and decision-making under constraints

Typical Uses

Used to design intelligent systems that perceive, learn, reason, and act on information.

Applications

  • Classification and prediction
  • Robotics and planning
  • Natural language and search systems

References

Recommended Textbooks

68T40 Robotics

Overview

This topic examines robotics within artificial intelligence and machine learning methods, focusing on the main concepts, representational choices, and standard questions used in modern research and practice. It provides a concise starting point for understanding how the topic fits into the wider field.

Related Wikipedia Page

Artificial intelligence (Wikipedia)

Useful Links

Key Ideas

  • Representation of knowledge and uncertainty
  • Learning from data with statistical and symbolic methods
  • Planning and decision-making under constraints

Typical Uses

Used to design intelligent systems that perceive, learn, reason, and act on information.

Applications

  • Classification and prediction
  • Robotics and planning
  • Natural language and search systems

References

Recommended Textbooks

68T42 Agent technology and multi-agent systems

Overview

This topic examines agent technology and multi-agent systems within artificial intelligence and machine learning methods, focusing on the main concepts, representational choices, and standard questions used in modern research and practice. It provides a concise starting point for understanding how the topic fits into the wider field.

Related Wikipedia Page

Artificial intelligence (Wikipedia)

Useful Links

Key Ideas

  • Representation of knowledge and uncertainty
  • Learning from data with statistical and symbolic methods
  • Planning and decision-making under constraints

Typical Uses

Used to design intelligent systems that perceive, learn, reason, and act on information.

Applications

  • Classification and prediction
  • Robotics and planning
  • Natural language and search systems

References

Recommended Textbooks

68T45 Machine vision and scene understanding

Overview

This topic examines machine vision and scene understanding within artificial intelligence and machine learning methods, focusing on the main concepts, representational choices, and standard questions used in modern research and practice. It provides a concise starting point for understanding how the topic fits into the wider field.

Related Wikipedia Page

Artificial intelligence (Wikipedia)

Useful Links

Key Ideas

  • Representation of knowledge and uncertainty
  • Learning from data with statistical and symbolic methods
  • Planning and decision-making under constraints

Typical Uses

Used to design intelligent systems that perceive, learn, reason, and act on information.

Applications

  • Classification and prediction
  • Robotics and planning
  • Natural language and search systems

References

Recommended Textbooks

68T50 Natural language processing

Overview

This topic examines natural language processing within artificial intelligence and machine learning methods, focusing on the main concepts, representational choices, and standard questions used in modern research and practice. It provides a concise starting point for understanding how the topic fits into the wider field.

Related Wikipedia Page

Artificial intelligence (Wikipedia)

Useful Links

Key Ideas

  • Representation of knowledge and uncertainty
  • Learning from data with statistical and symbolic methods
  • Planning and decision-making under constraints

Typical Uses

Used to design intelligent systems that perceive, learn, reason, and act on information.

Applications

  • Classification and prediction
  • Robotics and planning
  • Natural language and search systems

References

Recommended Textbooks

68T52 Fuzzy sets and logic in artificial intelligence

Overview

This topic examines fuzzy sets and logic in artificial intelligence within artificial intelligence and machine learning methods, focusing on the main concepts, representational choices, and standard questions used in modern research and practice. It provides a concise starting point for understanding how the topic fits into the wider field.

Related Wikipedia Page

Artificial intelligence (Wikipedia)

Useful Links

Key Ideas

  • Representation of knowledge and uncertainty
  • Learning from data with statistical and symbolic methods
  • Planning and decision-making under constraints

Typical Uses

Used to design intelligent systems that perceive, learn, reason, and act on information.

Applications

  • Classification and prediction
  • Robotics and planning
  • Natural language and search systems

References

Recommended Textbooks

68T99 None of the above

Overview

This topic examines none of the above within artificial intelligence and machine learning methods, focusing on the main concepts, representational choices, and standard questions used in modern research and practice. It provides a concise starting point for understanding how the topic fits into the wider field.

Related Wikipedia Page

Artificial intelligence (Wikipedia)

Useful Links

Key Ideas

  • Representation of knowledge and uncertainty
  • Learning from data with statistical and symbolic methods
  • Planning and decision-making under constraints

Typical Uses

Used to design intelligent systems that perceive, learn, reason, and act on information.

Applications

  • Classification and prediction
  • Robotics and planning
  • Natural language and search systems

References

Recommended Textbooks