CMSC 471
Fall 2015
Class #6
Tues 9/15/15
Local Search
Outline
Iterative improvement methods
Hill climbing
Simulated annealing
Local beam search
Genetic algorithms
Online search
Local Search
Chapter 4
Iterative Improvement Search
Another approach to sea

;Author: Du Nguyen
;Hw 1 part III
;-; A less two function which return a value is lesser than 2.
(defun lesstwo (n) (- n 2)
; A fact function which return the factorial of the argument.
(defun fact (n)
(if (= N 1)
1
(* N (fact (- N 1)
; A my third functio

CMSC 471
Fall 2015
Class #14
Tuesday, October 13, 2015
Machine Learning I:
Decision Trees
Todays Class
Machine learning
What is ML?
Inductive learning
Supervised
Unsupervised
Decision trees
Later well cover Bayesian learning, nave Bayes, and
BN lea

Multi-Agent Systems:
Overview and Research Directions
CMSC 471
October 8, 2015
Multi-Agent Systems
Russell & Norvig Ch. 17.5-17.6
Outline
Whats an Agent?
Multi-Agent Systems
(Cooperative multi-agent systems)
Competitive multi-agent systems
MAS Resear

[CS570 Artificial Intelligence]
Homework #2 Solution
Written by Jaedeug Choi
1.
Problem 5.6 in the book
Solve the cryptarithmetic problem in Figure 5.2 by hand, using backtracking, forward checking, and the
MRV and least-constraining-value heuristics. (10

CMSC 471
Fall 2015
Class #10
Tuesday, 9/29/15
Probabilistic Reasoning
Todays Class
Probability theory
Bayesian inference
From the joint distribution
Using independence/factoring
From sources of evidence
2
Bayesian Reasoning
Chapter 13
3
Sources of Un

Decision Making Under
Uncertainty
CMSC 471 Fall 2015
Class #12 Tuesday, October 6, 2015
R&N, Chapters 15.1-15.2.1, 16.1-16.3
material from Lise Getoor, Jean-Claude
Latombe, and Daphne Koller
1
MODELING UNCERTAINTY
OVER TIME
2
Temporal Probabilistic
Agent

CMSC 471
Fall 2015
Class #7
Thursday 9/17
Constraint Satisfaction
Constraint
Satisfaction
Russell & Norvig Ch. 6.1-6.4
2
Todays Class
Constraint Processing / Constraint Satisfaction Problem
(CSP) paradigm
Algorithms for CSPs
Backtracking (systematic se

Du Nguyen
CMSC 471
20/10/2015
HW 3
3.14 Which of the following are true and which are false? Explain your answers.
a. Depth-first search always expands at least as many nodes as A* search with an admissible
heuristic.
- FALSE. depth-first may be lucky to