Problem solving
Patterns designed to solve user problems
Probabilistic / Statistical Reasoning
Represent and reason with uncertainty using probabilistic models and statistical methods.
Search & Optimization
Techniques for finding optimal or near-optimal solutions in large search spaces.
Evolutionary & Nature-Inspired Computation
Search methods inspired by biological or collective natural processes.
Supervised Learning
Methods that learn mappings from inputs to labeled outputs.
Deep Learning Architectures
Specific neural network architectures that are widely used.
Unsupervised Learning
Techniques that discover structure in data without labels.
Reinforcement Learning
Agent-based learning from interaction with environments guided by rewards.
Symbolic / Logic-Based Reasoning
Rule- and logic-based techniques for explicit symbolic reasoning.
Graphical / Structured Probabilistic Models
Models that represent dependencies between variables as graphs.





































































