Artificial Intelligence
Natural language processing <>
Information extraction  <>
Machine translation <>
Discourse, dialogue and pragmatics <>
Natural language generation <>
Speech recognition <>
Lexical semantics <>
Phonology / morphology <>
Language resources <>

Knowledge representation and reasoning <>
Description logics <>
Semantic networks <>
Nonmonotonic, default reasoning and belief revision <>
Probabilistic reasoning <>
Vagueness and fuzzy logic <>
Causal reasoning and diagnostics <>
Temporal reasoning <>
Cognitive robotics <>
Ontology engineering <>
Logic programming and answer set programming <>
Spatial and physical reasoning <>
Reasoning about belief and knowledge <>

Planning and scheduling <>
Planning for deterministic actions <>
Planning under uncertainty <>
Multi-agent planning <>
Planning with abstraction and generalization <>
Robotic planning <>
<>Evolutionary robotics <>

Search methodologies <>
Heuristic function construction <>
Discrete space search <>
Continuous space search <>
Randomized search <>
Game tree search <>
Abstraction and micro-operators <>
Search with partial observations <>

Control methods <>
Robotic planning <>
<>Evolutionary robotics <>
Computational control theory <>
Motion path planning <>

Philosophical/theoretical foundations of artificial intelligence <>
Cognitive science <>
Theory of mind <>

Distributed artificial intelligence <>
Multi-agent systems <>
Intelligent agents <>
Mobile agents <>
Cooperation and coordination <>

Computer vision <>
Computer vision tasks <>
Image and video acquisition <>
Computer vision representations <>
Computer vision problems <>


Machine learning <>
Supervised learning <>
<>Ranking <>
<>Supervised learning by classification <>
<>Supervised learning by regression <>
<>Structured outputs <>
<>Cost-sensitive learning <>
Unsupervised learning <>
<>Cluster analysis <>
<>Anomaly detection <>
<>Mixture modeling <>
<>Topic modeling <>
<>Source separation <>
<>Motif discovery <>
<>Dimensionality reduction and manifold learning <>
Reinforcement learning <>
<>Sequential decision making <>
<>Inverse reinforcement learning <>
<>Apprenticeship learning <>
<>Multi-agent reinforcement learning <>
<>Adversarial learning <>
Multi-task learning <>
<>Transfer learning <>
<>Lifelong machine learning <>
<>Learning under covariate shift <>
Learning settings <>
<>Batch learning <>
<>Online learning settings <>
<>Learning from demonstrations <>
<>Learning from critiques <>
<>Learning from implicit feedback <>
<>Active learning settings <>
<>Semi-supervised learning settings <>
Machine learning approaches <>
<>Classification and regression trees <>
<>Kernel methods <>
<><>Support vector machines <>
<><><>Gaussian processes <>
<><><>Neural networks <>
<>Logical and relational learning <>
<>Inductive logic learning <>
<>Statistical relational learning <>
<>Learning in probabilistic graphical models <>
<><>Maximum likelihood modeling <>
<><>Maximum entropy modeling <>
<><>Maximum a posteriori modeling <>
<><>Mixture models <>
<><>Latent variable models <>
<><>Bayesian network models <>
<>Learning linear models <>
<><>Perceptron algorithm <>
<>Factorization methods <>
<><>Non-negative matrix factorization <>
<><><>Factor analysis <>
<><><>Principal component analysis <>
<><><>Canonical correlation analysis <>
<><><>Latent Dirichlet allocation <>
Rule learning <>
Instance-based learning <>
Markov decision processes <>
Partially-observable Markov decision processes <>
Stochastic games <>
Learning latent representations <>
<>Deep belief networks <>
Bio-inspired approaches <>
<>Artificial life <>
<>Evolvable hardware <>
<>Genetic algorithms <>
<>Genetic programming <>
<>Evolutionary robotics <>
<>Generative and developmental approaches <>
Machine learning algorithms <>
<>Dynamic programming for Markov decision processes <>
<>Value iteration <>
<>Q-learning <>
<>Policy iteration <>
<>Temporal difference learning <>
<>Approximate dynamic programming methods <>
<>Ensemble methods <>
<>Boosting <>
<>Bagging <>
<>Spectral methods <>
<>Feature selection <>
<>Regularization <>
<>Cross-validation <>