20_Summary - 12/4/2009 What have we done? Learning Theory:...

Info iconThis preview shows pages 1–2. Sign up to view the full content.

View Full Document Right Arrow Icon
12/4/2009 1 The Rest of AI Summary What have we done? Learning Theory: Generalization Error Bounds, Overfitting, CV Algorithms: Decision Tree, KNN, Perceptron, NN, SVM Unsupervised learning; K Means Acting Search – Uninformed Search: DFS, BFS, IDS, Bi Directional –Heuristic Search: Greedy, A*, IDS* Theory: Markov Decision Processes Reinforcement Learning: TD, ADP Planning: Situation Calculus, STRIPS, Partial Order Planning Reasoning Logic: FOL and Propositional Reasoning: Resolution proofs – Local Search: Hill Climbing, Simulated Annealing – Global Search, building blocks, partial solutions –Constraint Satisfaction –Adversarial Search What have we NOT done? Applications Acting: Production planning in factories Automated assembly Learning: Spam filtering Cd i t d fddt t i Credit card fraud detection Market basket analysis Reasoning: Embedded diagnosis systems Interactive help systems Software verification What is lacking? Achieving everything together! A learning system that has knowledge and can plan and act under uncertainty.
Background image of page 1

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
Image of page 2
This is the end of the preview. Sign up to access the rest of the document.

Page1 / 3

20_Summary - 12/4/2009 What have we done? Learning Theory:...

This preview shows document pages 1 - 2. Sign up to view the full document.

View Full Document Right Arrow Icon
Ask a homework question - tutors are online