Search Algorithms in Intelligent Agents

Presented by

H. Joshi and J. McAdams

{hmjoshi, jamcadams} @ualr.edu

CPSC7321 – Distributed OS Final Presentation

© 2003 UALR

Outline Introduction Search Algorithms

Traditional Heuristic Asynchronous Algorithm Comparison

Semantic Search Conclusion Demo

Introduction

Current Algorithms Text Based File Name Based Frame Based – NLP

Semantic Search

Traditional Search Algorithms

Breadth-First

Depth-First

Depth-First, Iterative Deepening

Bidirectional

Breadth-First

1

4 5 6 7

2 3

8 9 10 11 12 13 14 15

Depth-First

11 1

2 3

1 1

2 2 3

4 5

1 1

2 2 3

4 3 5

6 7

1 1

2 2 3

4 3 5

6 4 7

1 1

2 2 3

4 3 5

6 4 7 5

1 1

2 2 3

4 3 5 6

6 4 7 5 8 9

1 1

2 2 3

4 3 5 6

6 4 7 5 8 7 9

1 1

2 2 3

4 3 5 6

6 4 7 5 8 7 9 8

1 1

2 2 3 9

4 3 5 6 10 11

6 4 7 5 8 7 9 8

1 1

2 2 3 9

4 3 5 6 10 10 11

6 4 7 5 8 7 9 8 12 13

1 1

2 2 3 9

4 3 5 6 10 10 11

6 4 7 5 8 7 9 8 12 11 13

1 1

2 2 3 9

4 3 5 6 10 10 11

6 4 7 5 8 7 9 8 12 11 13 12

1 1

2 2 3 9

4 3 5 6 10 10 11 13

6 4 7 5 8 7 9 8 12 11 13 12 14 15

1 1

2 2 3 9

4 3 5 6 10 10 11 13

6 4 7 5 8 7 9 8 12 11 13 12 14 14 15

1 1

2 2 3 9

4 3 5 6 10 10 11 13

6 4 7 5 8 7 9 8 12 11 13 12 14 14 15 15

Depth-First, Iterative Deepening1 1Pass 1

1 1

2 2 3 9

Pass 2

1 1

2 2 3 9

4 3 5 6 10 10 11 13

Pass 3

1 1

2 2 3 9

4 3 5 6 10 10 11 13

6 4 7 5 8 7 9 8 12 11 13 12 14 14 15 15

Pass 4

Heuristic Search Algorithms Generate and Test Hill-Climbing Best-First A* Iterative Deepening A* Beam Means-Ends Constraint

Generate and Test

Solution Set

Problem

Solution Set

Problem Generate Solution

Solution Set

Problem Generate Solution Is Match?

Solution Set

Problem Generate Solution Is Match?

No

Solution Set

Problem Generate Solution Is Match?

Solution Set

Problem Generate Solution Is Match?

Solution Set

Problem Generate Solution Is Match? ResultYes

Solution Set

Problem Generate Solution Is Match? ResultYes

No

Hill-Climbing

A

B CD

E

1 2

4

145

3

Case 1

Path Taken:

3

Initial Node: AGoal Node: E

A

B CD

E

1 2

4

145

3

Case 1

Path Taken: A - B

3

Initial Node: AGoal Node: E

A

B CD

E

1 2

4

145

3

Case 1

Path Taken: A - B - D

3

Initial Node: AGoal Node: E

A

B CD

E

1 2

4

145

3

Case 1

Path Taken: A - B - D - C

3

Initial Node: AGoal Node: E

A

B CD

E

1 2

4

145

3

Case 1

Path Taken: A - B - D - C - E

3

Initial Node: AGoal Node: E

A

B CD

E

1 2

4

145

3

Case 1

Path Taken: A - B - D - C - EOptimal Path: A - C - E

3

Initial Node: AGoal Node: E

A

B CD

E

1 2

4

145

3

Case 2

Path Taken:

2

A

B CD

E

1 2

4

145

3

Case 2

Path Taken: A - B

2

A

B CD

E

1 2

4

145

3

Case 2

Path Taken: A - B - D

2

A

B CD

E

1 2

4

145

3

Case 2

Path Taken: A - B - D - A

2

A

B CD

E

1 2

4

145

3

Case 2

Path Taken: A - B - D - AOptimal Path: A - C - E

2

Best-First1

C

1 1

C

2

A

3

F

1 1

C

2 2

A

3

F

5

B

4

G

1 1

C

2 2

A

3 4

F

5 3

B

4

G

7

R

6

H

1 1

C

2 2

A

3 4

F

9

J

8

V

5 3

B

4

G

7

R

6

H

1 1

C

2 2

A

3 4

F

9

J

8

V

5 3

B

4 5

G

7

R

6

H

11

C

10

T

1 1

C

2 2

A

3 4

F

9

J

8

V

5 3

B

4 5

G

7

R

6

H

11 6

C

10

T

1 1

C

2 2

A

3 4

F

9

J

8

V

5 3

B

4 5

G

7

R

6 7

H

11 6

C

10

T

1 1

C

2 2

A

3 4

F

9 8

J

8

V

5 3

B

4 5

G

13

N

12

Q

7

R

6 7

H

11 6

C

10

T

1 1

C

2 2

A

3 4

F

9 8

J

8

V

5 3

B

4 5

G

13 9

N

12

Q

7

R

6 7

H

11 6

C

10

T

1 1

C

2 2

A

3 4

F

9 8

J

8

V

5 3

B

4 5

G

13 9

N

12 10

Q

7

R

6 7

H

11 6

C

10

T

1 1

C

2 2

A

3 4

F

9 8

J

8

V

5 3

B

4 5

G

13 9

N

12 10

Q

7 11

R

6 7

H

11 6

C

10

T

1 1

C

2 2

A

3 4

F

9 8

J

8

V

5 3

B

4 5

G

13 9

N

12 10

Q

7 11

R

6 7

H

11 6

C

10 12

T

1 1

C

2 2

A

3 4

F

9 8

J

8 13

V

5 3

B

4 5

G

13 9

N

12 10

Q

15

E

14

A

7 11

R

6 7

H

11 6

C

10 12

T

1 1

C

2 2

A

3 4

F

9 8

J

8 13

V

5 3

B

4 5

G

13 9

N

12 10

Q

15

E

14 14

A

7 11

R

6 7

H

11 6

C

10 12

T

1 1

C

2 2

A

3 4

F

9 8

J

8 13

V

5 3

B

4 5

G

13 9

N

12 10

Q

15 15

E

14 14

A

7 11

R

6 7

H

11 6

C

10 12

T

A*

A

EFG

DBH

C

f(n) = 17g(n) = 0h(n) = 17A

EFG

DBH

C

H A

EFG

DB

CA

EFG

DBH

C

f(n) = 17g(n) = 0h(n) = 17

f(n) = 19g(n) = 1h(n) = 18

f(n) = 11g(n) = 1h(n) = 10

A

EFG

DBH

C

A C

EFG

DBH

A B

EFG

DH

C

H A

EFG

DB

CA

EFG

DBH

C

f(n) = 17g(n) = 0h(n) = 17

f(n) = 19g(n) = 2h(n) = 17

f(n) = 19g(n) = 1h(n) = 18

f(n) = 11g(n) = 1h(n) = 10

f(n) = 2g(n) = 2h(n) = 0

Asynchronous Search Algorithms

Asynchronous Dynamic Programming

Learning Real-Time A*

Real-Time Multi-agent

Asynchronous Dynamic Programming

Init -1

C -1

A -1

D -1

B -1

Goal 0

2

5

12

34

3

Cycle 1

Init -1

C -1

A -1

D 5

B 3

Goal 0

2

5

15

34

3

1

Cycle 2

Init -1

C 6

A 7

D 4

B 3

Goal 0

2

5

15

34

3

1

Cycle 3

Init 9

C 5

A 7

D 4

B 3

Goal 0

2

5

15

34

3

1

Cycle 4

Init 8

C 5

A 7

D 4

B 3

Goal 0

2

5

15

34

3

1

Cycle 5

Learning Real-Time A*

Init

B

A3

4

Cycle 1

Init

B

A3

4D

C4

5

Cycle 2

Init

A5

4D

C4

5F

E4

3

B

Cycle 3

Init

B

A

5

4

D

C4

5F

E4

3

H

G1

3

J

I4

2

Cycle 4

Init

B

A

5

2

D

C4

5F

E4

3

H

G1

3

J

I4

2

Goal0

L

K2

1

Cycle 5

Features For Comparison Latency of the network affecting search process Searching for semantically correct information Relevance of the information Order of complexity of an algorithm Suitable for Text, graphics, audio, video (multimedia) contents

Does the algorithm consider aging of information and outdated/obsolete information

Distributiveness of an algorithm

Algorithm ComparisonAlgorithm Time Memory Complete Optimal

Breadth-First O(bd) O(bd) Yes Yes

Depth-First O(bd) O(d) No No

Depth-First Iterative-Deepening O(bd) O(d) Yes Yes

Bidirectional O(bd/2) O(bd/2) Yes Yes

Hill-Climbing O(bd) O(1) – O(bd) No No

Best-First O(bd) O(bd) Yes No

A* O(bd) O(bd) Yes Yes

Iterative-Deepening-A* O(bd) O(d) Yes Yes

Beam Search O(nd) O(nd) No No

Means-Ends O(bd) O(bd) No No

Generate and Test O(((bd!)/((bd-d)!))/2) O(d) Yes No

Asynchronous Dynamic O(bd) O(1) Yes Yes

Learning Real-Time A* O(bd) O(bd) Yes Yes

Real-Time A* O(bd) O(bd) Yes No

Semantic Intelligent Search Agent

Conclusion

Having the right tool for the job

Meaningful searching

Demo and Questions