CSE 473
Lecture 5
Heuristics
CSE AI Faculty
Last Time: A* Search
Use an evaluation function
f(n) for node n.
f(n) = estimated total cost
of path thru n to goal
Problem: Search for
shortest path from
CSE 473
Lecture 16
Markov Decision Processes (MDPs)
Part II
CSE AI faculty + Chris Bishop, Dan Klein, Stuart Russell, Andrew Moore
Recall: Markov Decision Processes
An MDP is defined by:
A set of s
CSE 473
Lecture 15
Markov Decision Processes (MDPs)
CSE AI faculty + Chris Bishop, Dan Klein, Stuart Russell, Andrew Moore
Course Overview: Where are we?
Introduction & Agents
Search and Heuristics
A
CSE 473
Lecture 13
Chapter 9
Reasoning with First-Order Logic
Chaining
Resolution
Compilation to SAT
CSE AI faculty
FOL Reasoning: Motivation
What if we want to use modus ponens?
Propositional Logic
CSE 473
Lecture 9
Logic and Reasoning
CSE AI Faculty
Outline
(Chapter 7)
Knowledge-based agents
Wumpus world
Logic in general
Propositional logic
Inference, validity, equivalence
and satisfiability
CSE 473
Chapter 7
Inference Techniques for
Logical Reasoning
Recall: Wumpus World
Wumpus
You
(Agent)
2
Wumpusitional Logic
Proposition Symbols and Semantics:
Let Pi,j be true if there is a pit in [i,
CSE 473
Lecture 11
Chapter 7
Inference in Propositional Logic
CSE AI faculty
Recall: Propositional Logic Terminology
Literal
= proposition symbol or its negation
E.g., A, A, B, B, etc. (positive vs.
CSE 473
Artificial Intelligence (AI)
Rajesh Rao (Instructor)
Yi-Shu Wei (TA)
Hunter Whalen (TA)
http:/www.cs.washington.edu/473
Based on slides by UW CSE AI faculty, Dan Klein, Stuart Russell, Andrew
CSE 473
Chapter 3
Problem Solving using Search
First, they do an on-line search
CSE AI Faculty
Pac-Man as an Agent
2
1
The CSE 473 Pac-Man
Projects
Originally developed at UC Berkeley:
http:/www-inst
CSE 473
Lecture 7
Playing Games with Minimax and
Alpha-Beta Search
CSE AI Faculty
Today
Adversarial Search
Minimax recap
- search
Evaluation functions
State of the art in game playing
1
Recall: Game
CSE 473
Lecture 8
Adversarial Search: Expectimax
and Expectiminimax
Based on slides from CSE AI Faculty + Dan Klein, Stuart Russell, Andrew Moore
Where we have been and
where we are headed
Blind Sear
Lecture 2
Agents & Environments
(Chap. 2)
Based on slides by UW CSE AI faculty, Dan Klein, Stuart Russell, Andrew Moore
Outline
Agents and environments
Rationality
PEAS specification
Environment types
CSE 473
Chaps 4.1 & 5
Local Search and Games
CSE AI Faculty
Local search algorithms
What if path to goal is irrelevant? Only
interested in finding the goal state !
E.g., N-queens: Put N queens on an