# Classical AI Notes Hub > [!Note] > Hub consolidating notes on **Classical (Symbolic) AI** — the pre-deep-learning > foundation of the field: search, logic, constraint satisfaction, planning, > game playing, and probabilistic reasoning. Russell & Norvig is the canonical > reference. ## 1. Search and Problem Solving - [[State Space Search]] - [[Uninformed Search]] - [[Breadth-First Search]] · [[Depth-First Search]] · [[Iterative Deepening Search]] · [[Uniform Cost Search]] - [[Heuristic Search]] - [[A Star Algorithm]] · [[IDA Star Algorithm]] - [[Greedy Best-First Search]] · [[Beam Search]] - [[Hill Climbing]] - [[Admissibility and Consistency of Heuristics]] --- ## 2. Logic and Knowledge Representation - [[Propositional Logic]] - [[First-Order Logic]] - [[Inference Rules]] - [[Resolution Inference]] - [[Forward and Backward Chaining]] - [[Knowledge Representation]] - [[Ontologies and Semantic Networks]] --- ## 3. Constraint Satisfaction - [[Constraint Satisfaction Problem]] - [[Backtracking Search]] - [[Arc Consistency AC-3]] - [[Constraint Propagation]] --- ## 4. Planning - [[Classical Planning]] - [[STRIPS]] - [[PDDL]] - [[Heuristic Planning]] - [[GRAPHPLAN]] - [[HTN Planning]] --- ## 5. Game Playing - [[Minimax Algorithm]] - [[Alpha-Beta Pruning]] - [[Monte Carlo Tree Search]] - [[Evaluation Function]] --- ## 6. Probabilistic Reasoning - [[Bayes Theorem]] - [[Bayesian Network]] - [[D-Separation]] - [[Variable Elimination]] - [[Hidden Markov Model]] - [[Markov Network]]