Outline of artificial intelligence

AI algorithms and techniques

Search

• Discrete search algorithms
• * Uninformed search
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• * Informed search
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• * Adversarial search
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• * Logic as search
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• * Planning as search
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  Optimization search

• Optimization algorithms
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• Evolutionary computation
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• Society based learning algorithms.
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  Logic

• Logic and automated reasoning
• * Programming using logic
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• ** See "Logic as search" above.
• * Forms of Logic
• ** Propositional logic
• ** First-order logic
• *** First-order logic with equality
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• ** Fuzzy logic
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• *** Perceptual Computing –
• ** Default reasoning and other solutions to the frame problem and qualification problem
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• *** Abductive reasoning
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• * Domain specific logics
• ** Representing categories and relations
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• ** Representing events and time
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• ** Causes and effects
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• ** Knowledge about knowledge
• *** Belief revision
• *** Modal logics
• *** paraconsistent logics
• * Planning using logic
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• * Learning using logic
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• * General logic algorithms
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  Other symbolic knowledge and reasoning tools

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• Commonsense knowledge

  Probabilistic methods for uncertain reasoning

• Stochastic methods for uncertain reasoning:
• * Bayesian networks
• * Bayesian inference algorithm
• * Bayesian learning and the expectation-maximization algorithm
• * Bayesian decision theory and Bayesian decision networks
• Probabilistic perception and control:
• * Dynamic Bayesian networks
• * Hidden Markov model
• * Kalman filters
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• Decision tools from economics:
• * Decision theory
• * Decision analysis
• * Information value theory
• * Markov decision processes
• * Dynamic decision networks
• * Game theory
• * Mechanism design
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  Classifiers and statistical learning methods

• Classifier and Statistical classification
• * Alternating decision tree
• * Artificial neural network
• * K-nearest neighbor algorithm
• * Kernel methods
• ** Support vector machine
• * Naive Bayes classifier

  Artificial neural networks

• Artificial neural networks
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• ** feedforward neural networks
• *** Perceptrons
• *** Multi-layer perceptrons
• *** Radial basis networks
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• ** Recurrent neural networks
• *** Long short-term memory
• *** Hopfield networks
• *** Attractor networks
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• * Learning algorithms for neural networks
• ** Hebbian learning
• ** Backpropagation
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• ** Competitive learning
• ** Supervised backpropagation
• ** Neuroevolution
• ** Restricted Boltzmann machine

  Biologically based or embodied

• Developmental robotics
• Situated AI
• Artificial immune systems

• Cognitive architecture and multi-agent systems

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• * AERA
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• Distributed artificial intelligence –
• Multi-agent system –

• Philosophy

Definition of AI

• Pei Wang's definition of artificial intelligence
• Dartmouth proposal
• Turing test
• * Computing Machinery and Intelligence
• Intelligent agent and rational agent
• * Action selection
• AI effect
• Synthetic intelligence

  Classifying AI

• Symbolic vs sub-symbolic AI
• * Symbolic AI
• * Physical symbol system
• * Dreyfus' critique of AI
• * Moravec's paradox
• Elegant and simple vs. ad-hoc and complex
• * Neat vs. Scruffy
• * Society of Mind
• * The Master Algorithm
• Level of generality and flexibility
• * Artificial general intelligence
• * Narrow AI
• Level of precision and correctness
• * Soft computing
• * "Hard" computing
• Level of intelligence
• * Progress in artificial intelligence
• * Superintelligence
• Level of consciousness, mind and understanding
• * Chinese room
• * Hard problem of consciousness
• * Computationalism
• * Functionalism
• * Robot rights
• * User illusion
• * Artificial consciousness

  Goals and applications

General intelligence

• Artificial general intelligence
• * AI-complete

  Reasoning and Problem Solving

• Automated reasoning
• Mathematics
• * Automated theorem prover
• * Computer-assisted proof –
• * Computer algebra
• General Problem Solver
• Expert system –
• * Decision support system –
• ** Clinical decision support system –

  Knowledge representation

• Knowledge representation
• Knowledge management
• Cyc

  Planning

• Automated planning and scheduling
• Strategic planning
• Sussman anomaly –

  Learning

• Machine learning –
• * Constrained Conditional Models –
• * Deep learning –
• * Neural modeling fields –
• * Supervised learning –
• * Weak supervision –
• * Unsupervised learning –

  Natural language processing

• Natural language processing –
• * Chatterbots –
• * Language identification –
• * Large language model –
• * Natural language user interface –
• * Natural language understanding –
• * Machine translation –
• * Statistical semantics –
• * Question answering –
• * Semantic translation –
• * Concept mining –
• ** Data mining –
• ** Text mining –
• ** Process mining –
• * E-mail spam filtering –
• * Information extraction –
• ** Named-entity extraction –
• *** Coreference resolution –
• *** Named-entity recognition –
• *** Relationship extraction –
• *** Terminology extraction –

  Perception

• Machine perception
• Pattern recognition –
• Computer Audition –
• * Speech recognition –
• * Speaker recognition –
• Computer vision –
• * Image processing
• * Intelligent word recognition –
• * Object recognition –
• * Optical mark recognition –
• ** Handwriting recognition –
• ** Optical character recognition –
• *** Automatic number plate recognition –
• * Information extraction –
• ** Image retrieval –
• *** Automatic image annotation –
• * Facial recognition systems –
• ** Silent speech interface –
• ** Activity recognition –
• Percept

  Robotics

• Robotics –
• * Behavior-based robotics –
• * Cognitive –
• * Cybernetics –
• * Developmental robotics –
• * Evolutionary robotics –

  Control

• Intelligent control
• Self-management –
• * Autonomic Computing –
• * Autonomic Networking –

  Social intelligence

• Affective computing
• Kismet

  Game playing

• Game artificial intelligence –
• * Computer game bot – computer replacement for human players.
• * Video game AI –
• ** Computer chess –
• ** Computer Go –
• * General game playing –
• * General video game playing –

  Creativity, art and entertainment

• Artificial creativity
• Artificial intelligence art
• Creative computing
• Generative artificial intelligence
• Uncanny valley
• Music and artificial intelligence
• Computational humor
• Chatbot

  Integrated AI systems

• AIBO - Sony's robot dog. It integrates vision, hearing and motorskills.
• Asimo – humanoid robot developed by Honda, capable of walking, running, negotiating through pedestrian traffic, climbing and descending stairs, recognizing speech commands and the faces of specific individuals, among a growing set of capabilities.
• - A.I. embodied humanoid in an augmented reality environment.
• Cog - M.I.T. humanoid robot project under the direction of Rodney Brooks.
• QRIO - Sony's version of a humanoid robot.
• TOPIO, TOSY's humanoid robot that can play ping-pong with humans.
• Watson – computer developed by IBM that played and won the game show Jeopardy! It is now being used to guide nurses in medical procedures.
• * Purpose: Open domain question answering
• * Technologies employed:
• ** Natural language processing
• ** Information retrieval
• ** Knowledge representation
• ** Automated reasoning
• ** Machine learning
• Project Debater - artificially intelligent computer system, designed to make coherent arguments, developed at IBM's lab in Haifa, Israel.

  Intelligent personal assistants

• Amazon Alexa -
• Assistant -
• Braina -
• Cortana -
• Google Assistant -
• Google Now -
• Mycroft -
• Siri -
• Viv -

  Other applications

• Artificial life – simulation of natural life through the means of computers, robotics, or biochemistry.
• Automatic target recognition –
• Diagnosis –
• Speech generating device –
• Vehicle infrastructure integration –
• Virtual Intelligence –

  History

• History of artificial intelligence
• Progress in artificial intelligence
• Timeline of artificial intelligence
• AI effect – as soon as AI successfully solves a problem, the problem is no longer considered by the public to be a part of AI. This phenomenon has occurred in relation to every AI application produced, so far, throughout the history of development of AI.
• AI winter – a period of disappointment and funding reductions occurring after a wave of high expectations and funding in AI. Such funding cuts occurred in the 1970s, for instance.
• Moore's law