Concept visualizations
Interactive visual aids for topics in AI: probabilistic reasoning, logical inference, agents, learning, game playing and constraint satisfaction.
Probabilistic Reasoning
Bayes' Theorem
Updating a prior belief with evidence to get a posterior: P(H|E) = P(E|H)·P(H) / P(E).
Naive Bayes
Classification with Bayes' rule under the assumption that features are conditionally independent given the class.
Bayesian Networks
Directed acyclic graphs that encode conditional dependencies and support probabilistic inference.
Logic & Inference
Agents
Learning & Decision Processes
Search & Game Playing
Deterministic Two-Player Zero-Sum Games
Minimax search over game trees where one player's gain is the other's loss.
Alpha-Beta Pruning
Skipping branches that cannot affect the minimax decision by tracking alpha and beta bounds.
Aspiration Windows
Searching with a narrow alpha-beta window around an expected value, re-searching on fail-high or fail-low.
Expectiminimax
Extending minimax with chance nodes to play stochastic games.
Monte Carlo Tree Search
Selection, expansion, simulation and backpropagation guided by UCT.