Bayesian networks
Chapter 14 Section 1 2
Bayesian networks
A simple, graphical notation for conditional independence assertions and hence for compact specification of full joint distributions Syntax:
a set of nodes, one per variable a directed, acyclic
Uncertainty
Let action At = leave for airport t minutes before flight Will At get me there on time? Problems:
1. 2. 3. 4. partial observability (road state, other drivers' plans, etc.) noisy sensors (traffic reports) uncertainty in action outcomes (flat t
Limitation of propositional logic
Propositional logic has very limited expressive power
(unlike natural language) E.g., cannot say "pits cause breezes in adjacent squares
except by writing one sentence for each square
First-order logic
Whereas proposi
Logical Agents
Chapter 7
Knowledge bases
Knowledge base (KB): set of sentences in a formal
language
Inference: deriving new sentences from the KB. E.g.:
A>5, B>A, B>5 Two blind persons, each bought 2 pairs of black socks and 2 pairs of white socks. Unf
Reading Material
Sections 3.3 3.5 Optimal Rectangle Packing: New Results By R. Korf (optional) Optimal Rectangle Packing: A Meta-CSP Approach (optional)
Sections 4.1 4.2
Best-first search
Idea: use an evaluation function f(n) for each node
estimate of
Reading assignment
Chapters 1, 2 Sections 3.1 and 3.2
What is artificial intelligence
Act rationally Integrate sub-areas in AI into intelligent agents
A full breath of potential applications Play games Control space-rovers Cure cancer Trade stocks Figh
So what is AI?
What is AI?
Views of AI fall into four categories: Thinking humanly Thinking rationally Acting humanly Acting rationally The textbook advocates "acting rationally"
State of the art: Game playing
State of the art: Robots
http:/robots.stanf
CSE 511A: Introduction to Artificial Intelligence
Lab 1 Due: October 14
1.
In this lab you will write a computer program to play a game, dots and boxes. (http:/en.wikipedia.org/wiki/Dots_and_boxes)
Starting with an empty grid of dots, players take turns,
CSE 511A: Introduction to Artificial Intelligence
Homework 3 (Due: 4pm, Nov 16)
a.
Download SATPLAN04 source code (http:/www.cs.rochester.edu/u/kautz/satplan/). Download the testing domains of the 4th International Planning Competition (http:/www.tzi.de/~
CSE 511A: Introduction to Artificial Intelligence
Homework 2 Due: October 12
Problem 4.7 Problem 4.9 Problem 4.12 Problem 5.6 Problem 5.8 Problem 5.11 (15%) (20%) (15%) (15%) (15%) (20%)
CSE 511A: Introduction to Artificial Intelligence
Homework 1 (Due: 4pm, Sept 16)
1. Problem 2.4 (note: you need to write arguments and general descriptions. Detailed mathematical analysis is not needed.) (12%) 2. Problem 3.7 (12%) 3. Problem 3.8 (12%) 4.
Adversarial Search
Chapter 6 Section 1 4
Games vs. search problems
"Unpredictable" opponent specifying a move for every possible opponent reply Time limits unlikely to find goal, must approximate Solutions
Search problems: a path Games: a strategy But h
Constraint Satisfaction Problems
Chapter 5
Chapter 5
1
Victor has been murdered, and Arthur, Bertram, and Carleton are suspects. Arthur says he did not do it. He says that Bertram was the victims friend but that Carleton hated the victim. Bertram says he
Beam-Stack Search:
Integrating Backtracking with Beam Search
11/13/09
Ring Zhou and Eric A.subtitle style Click to edit Master Hansen Presented by Paul Gross
Beam-Stack Search Overview
Complete, anytime algorithm O(dw) Memory Complexity
l
d = depth of o
Planning
Chapter 11 Yet another popular formulation for AI
Logic-based language One of the most structured formulations
Can be translate into less structured formulations such as state-space, CSP, SAT, etc.
What is Planning
Generate sequences of actio