Ai Exam 2

Front 1

Random Variables

Back 1

Take on one more more values (Ex Roll for a dice can be 1, 2 ,3 ..)

Front 2

Joint Variables

Back 2

Multiple Variable probabilities P(A, B)

Front 3

Marginialization

Back 3

Sum accross a row or column

Front 4

COnditional Probability

Back 4

Whats the probability of even A given that I know event B is true.

P(A|B) = P(A | B) / P(B)

Front 5

Marginilization General Rule

Back 5

P(X,Y,Z) and want P(X,Y) sum over Z

Front 6

Bayes Rule

Back 6

P(B|A) = [P(A|B) * P(B)] / P(A)

Front 7

Indepence

Back 7

P(A,B) = P(A) * P(B)

Front 8

Conditional Indepence

Back 8

P(A | B,C) =

[P(B | A) * P(C | A) * P(A)] / P(B,C)

Front 9

Naive Bayes

Back 9

P(Cause) * Prod(P(Event | Cause)) / [ Summation Over Cause (P(Cause) * Prod(P(Event | Cause))

Front 10

Iterative Vs. Search Solutions

Back 10

Iterative returns the goal as a solution while searches return the path

Front 11

Hill Climbing

Back 11

One dimension for each variable, try to find global max or global min, evaluation function says how good point is

Front 12

HIll Climbing - Random Restart

Back 12

Randomly restart each time

Front 13

Simulated Annealing

Back 13

Shake surface to move out of local mini/maxi and accept new state if better or based on decreasing probability if worse

Front 14

Beam Search

Back 14

Start multiple instances

Front 15

Genetic Algorithm

Back 15

Fitness Function - Increases!

Selection - Choose which parents based on fitness probability

Crossover - Choose a cut on parents and swap to make two new

Mutation - Randomly Flip bits

Front 16

Syntax

Back 16

How to construct sentences, their structure

Front 17

Semantics

Back 17

What the meaning of a sentnce is

Front 18

Atomic Sentence

Back 18

Truth value is assigned directly by model

Front 19

Complex Sentence

Back 19

Truth value assigned by the rules

Front 20

Valid Sentence

Back 20

Sentence true under all conditions

Front 21

Satisfiable Sentence

Back 21

Sentence is true under some conditions

Front 22

Unsatisfiable Sentence

Back 22

Sentence can never be true

Front 23

Inference

Back 23

Antecedent / Consequent

if we contain the Antecedent, we get the consequent

Front 24

A=>B Equivalent

Back 24

~A v B

Front 25

Modus Ponens

Back 25

A=>B, A

B

Front 26

And Introduction

Back 26

A,B

A & B

Front 27

Modus Tolens

Back 27

A=>B, ~B

~A

Front 28

Or Introduction

Back 28

A

A v B

Front 29

Unit Resolution

Back 29

A v B, ~B

A

Front 30

And Elimination

Back 30

A & B

A,B

Front 31

Forward Inference

Back 31

Insert something into KB, then derive all consequences

KB Tell is Slow, Ask is quick

Front 32

Backward Inference

Back 32

To see if Q is true, see if antecedents are truee

KB tesll is quick, ask is slow

Front 33

COnjunctive Normal Form

Back 33

X1 & X2 & X3

S.T.

X1 only contains ~, v

Front 34

Resolution

Back 34

Must be in conjunctive normal form, add opposite of what you want to KB, find contradiction using only unit resolution

Front 35

Constants

Back 35

Refer to exactly one thing

Front 36

Variables

Back 36

Reference constants

Front 37

Relational Predicates

Back 37

Return true or false:

MarriedTo(John,Doe)

Front 38

Functinoal Predicates

Back 38

Return an entity

FatherOf(John) = Joe

Front 39

For All Statements

Back 39

Always an impllication

Front 40

There Exists Statement

Back 40

Always an And statement

Front 41

For all and There Exists Equivalence

Back 41

~For All (Sentence)

There Exists ~(Sentence)

Front 42

For All Introduction

Back 42

Can substitue any term into for all statement

Front 43

There Exists Introduction - Skoelemizatino

Back 43

Can itnroduce one new constant into KB for there exists

Front 44

Propositionalization

Back 44

Make all possible isntantiations, hard to do

Front 45

Planning Languages

Back 45

State, Goal, Actions {Name, Parms, Precondition, Effect}

Front 46

Pllanning languages - Backward vs. Forward

Back 46

Start from goal vs start from initial