and/or graphs

21
AND/OR graphs Some problems are best Some problems are best represented as represented as achieving achieving subgoals, subgoals, some of which some of which achieved simultaneously and achieved simultaneously and independently (AND) independently (AND) Up to now, only dealt with OR Up to now, only dealt with OR options options Possess TV set Steal TV Earn Money Buy TV

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AND/OR graphs. Some problems are best represented as achieving subgoals, some of which achieved simultaneously and independently (AND) Up to now, only dealt with OR options. Possess TV set. Steal TV. Buy TV. Earn Money. Searching AND/OR graphs. - PowerPoint PPT Presentation

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Page 1: AND/OR graphs

AND/OR graphs Some problems are best represented as Some problems are best represented as

achieving achieving subgoals, subgoals, some of which some of which achieved simultaneously and achieved simultaneously and independently (AND)independently (AND)

Up to now, only dealt with OR optionsUp to now, only dealt with OR options

Possess TV set

Steal TV Earn Money Buy TV

Page 2: AND/OR graphs

Searching AND/OR graphs A solution in an AND-OR tree is a A solution in an AND-OR tree is a sub tree sub tree

whose whose leafsleafs are included in the goal set are included in the goal set

Cost function: sum of costs in AND nodeCost function: sum of costs in AND nodef(n) = f(nf(n) = f(n11) + f(n) + f(n22) + …. + f(n) + …. + f(nkk))

How can we extend A* to search AND/OR How can we extend A* to search AND/OR treestrees? The AO* algorithm.? The AO* algorithm.

Page 3: AND/OR graphs

AND/OR search We must examine several nodeWe must examine several nodess

simultaneously when choosing the next simultaneously when choosing the next movemove

A

B C D38

E F G H I J

17 9 27

(5) (10) (3) (4) (15) (10)

A

B C D(3)(4)

(5)(9)

Page 4: AND/OR graphs

AND/OR Best-First-Search Traverse the graph (from the initial node) Traverse the graph (from the initial node)

following the best current path.following the best current path. Pick one of the unexpanded nodes on that Pick one of the unexpanded nodes on that

path and expand it. Add its successors to path and expand it. Add its successors to the graph and compute the graph and compute ff for each of themfor each of them

Change the expanded node’s Change the expanded node’s ff value to value to reflect its successors. Propagate the reflect its successors. Propagate the change up the graph. change up the graph.

Reconsider the current best solution and Reconsider the current best solution and repeatrepeat until a solution is found until a solution is found

Page 5: AND/OR graphs

AND/OR Best-First-Search example

A

B C D(3)(4)

(5)(9)

A(5)

2.1.

A

B CD

E F(4) (4)(10)

(3)(9)

(4)

(10)

3.

Page 6: AND/OR graphs

AND/OR Best-First-Search example

B C D

G H E F(5) (7) (4) (4)(10)

(6)(12)

(4) (10)

4. A

Page 7: AND/OR graphs

A Longer path may be better

B C D

G H E F

A

JI

Unsolvable B C D

G H E F

A

JI

Unsolvable

Page 8: AND/OR graphs

Interacting Sub goals

C

D

E

A

(2)(5)

Page 9: AND/OR graphs

AO* algorithm

1.1. Let Let GG be a graph with only starting node be a graph with only starting node INIT.INIT.

2.2. Repeat the followings until INIT is labeled SOLVED Repeat the followings until INIT is labeled SOLVED or h(INIT) > FUTILITYor h(INIT) > FUTILITY

a)a) Select an unexpanded node from the most promising path Select an unexpanded node from the most promising path from from INIT (call it NODE)INIT (call it NODE)

b)b) Generate successors of NODE. If there are none, set Generate successors of NODE. If there are none, set h(NODE) = FUTILITY (i.e., NODE is unsolvable); h(NODE) = FUTILITY (i.e., NODE is unsolvable); otherwise for each SUCCESSOR that is not an ancestor of otherwise for each SUCCESSOR that is not an ancestor of NODE do the following:NODE do the following:

i.i. Add SUCCESSSOR to G.Add SUCCESSSOR to G.

ii.ii. If SUCCESSOR is a terminal node, label it SOLVED and set If SUCCESSOR is a terminal node, label it SOLVED and set h(SUCCESSOR) = 0.h(SUCCESSOR) = 0.

iii.iii. If SUCCESSPR is not a terminal node, compute its hIf SUCCESSPR is not a terminal node, compute its h

Page 10: AND/OR graphs

AO* algorithm (Cont.)c)c) Propagate the newly discovered information up the Propagate the newly discovered information up the

graph by doing the following: let S be set of SOLVED graph by doing the following: let S be set of SOLVED nodes or nodes whose h values have been changed nodes or nodes whose h values have been changed and need to have values propagated back to their and need to have values propagated back to their parents. Initialize S to Node. Until S is empty repeat parents. Initialize S to Node. Until S is empty repeat the followings:the followings:

i.i. Remove a node from S and call it CURRENT.Remove a node from S and call it CURRENT.ii.ii. Compute the cost of each of the arcs emerging from Compute the cost of each of the arcs emerging from

CURRENT. Assign minimum cost of its successors as its h.CURRENT. Assign minimum cost of its successors as its h.iii.iii. Mark the best path out of CURRENT by marking the arc that Mark the best path out of CURRENT by marking the arc that

had the minimum cost in step iihad the minimum cost in step iiiv.iv. Mark CURRENT as SOLVED if all of the nodes connected to Mark CURRENT as SOLVED if all of the nodes connected to

it through new labeled arc have been labeled SOLVEDit through new labeled arc have been labeled SOLVEDv.v. If CURRENT has been labeled SOLVED or its cost was just If CURRENT has been labeled SOLVED or its cost was just

changed, propagate its new cost back up through the graph. changed, propagate its new cost back up through the graph. So add all of the ancestors of CURRENT to S.So add all of the ancestors of CURRENT to S.

Page 11: AND/OR graphs

An Example

Page 12: AND/OR graphs

An Example

A(8)

Page 13: AND/OR graphs

An Example

C

DB

A

(8)(1)

(2)

[12]

4 5

5

[13]

Page 14: AND/OR graphs

An Example

C

DB

A

(8)(4)

(2)

[15]

4 5

5

[13]

2

Page 15: AND/OR graphs

An Example

C

DB

A

(3)(4)

G

E

(2)

(1)

(0)

[15]

4 5

52

2

4

[8]

Page 16: AND/OR graphs

An Example

C

DB

A

(4)(4)

G

E

(2)

(3)

(0)

[15]

4 5

52

22

4

[9]

3

Page 17: AND/OR graphs

An Example

C

DB

A

(4)

G

E

(2)

(3)

(0)

[15]

4 5

52

22

4

Solved

3

Solved

Solved

Page 18: AND/OR graphs

Considers the cost (> 0) for switching from one branch to Considers the cost (> 0) for switching from one branch to another in the searchanother in the search

Example: path finding in real lifeExample: path finding in real life

A CBDF E G

11 4 1 2 167

f(B) = 1 + 1 = 2f(B) = 1 + 1 = 2 (A) f(C) = 1 + 2 = (A) f(C) = 1 + 2 = 33

f(D) = 1 + 4 = 5f(D) = 1 + 4 = 5 (B) f(A) = 1 + 3 = (B) f(A) = 1 + 3 = 44

f(B) = 1 + 5 = 6 (A) f(C) = 1 + 2 = 3f(B) = 1 + 5 = 6 (A) f(C) = 1 + 2 = 3

f(A) = 1 + 6 = 7f(A) = 1 + 6 = 7 (C) f(E) = 1 + 7 = (C) f(E) = 1 + 7 = 88

f(B) = 1 + 5 = 6f(B) = 1 + 5 = 6 (A) f(C) = 1 + 8 = (A) f(C) = 1 + 8 = 99

f(D) = 1 + 4 = 5 f(D) = 1 + 4 = 5 (B) f(A) = 1 + 9 = (B) f(A) = 1 + 9 = 1010

f(F)=1+11= 12 (D) f(B) = 1 + 10 = 11f(F)=1+11= 12 (D) f(B) = 1 + 10 = 11

Real Time A*

Considers the cost (> 0) for switching from one branch to Considers the cost (> 0) for switching from one branch to another in the searchanother in the search

Example: path finding in real lifeExample: path finding in real life

A CBDF E G

11 4 1 2 167

f(B) = 1 + 1 = 2f(B) = 1 + 1 = 2 (A) f(C) = 1 + 2 = (A) f(C) = 1 + 2 = 33

f(D) = 1 + 4 = 5f(D) = 1 + 4 = 5 (B) f(A) = 1 + 3 = (B) f(A) = 1 + 3 = 44

f(B) = 1 + 5 = 6 (A) f(C) = 1 + 2 = 3f(B) = 1 + 5 = 6 (A) f(C) = 1 + 2 = 3

f(A) = 1 + 6 = 7f(A) = 1 + 6 = 7 (C) f(E) = 1 + 7 = (C) f(E) = 1 + 7 = 88

f(B) = 1 + 5 = 6f(B) = 1 + 5 = 6 (A) f(C) = 1 + 8 = (A) f(C) = 1 + 8 = 99

f(D) = 1 + 4 = 5 f(D) = 1 + 4 = 5 (B) f(A) = 1 + 9 = (B) f(A) = 1 + 9 = 1010

f(F)=1+11= 12 (D) f(B) = 1 + 10 = 11f(F)=1+11= 12 (D) f(B) = 1 + 10 = 11

Page 19: AND/OR graphs

Another Example

Current State = SCurrent State = S

f(A) = 3 + 5 = 8 f(A) = 3 + 5 = 8

f(B) = 2 + 4 = 6f(B) = 2 + 4 = 6

Current State = BCurrent State = B

f(S) = 2 + 8 = 10 f(S) = 2 + 8 = 10 f(A) = 4 + 5 = 9f(A) = 4 + 5 = 9

f(C) = 1 + 5 = 6f(C) = 1 + 5 = 6

f(E) = 4 + 2 = 6f(E) = 4 + 2 = 6

Current State = CCurrent State = C

f(H) = 2 + 4 = 6f(H) = 2 + 4 = 6

f(B) = 1 + 6 = 7f(B) = 1 + 6 = 7

A B

C

S

(4)

(4) D

(5)

2

(2)

G

(1)

E

(2)H

(0)

34

41

(5)

F

2 13

2

Page 20: AND/OR graphs

Current State = HCurrent State = H

f(C) = 2 + 7 = 9 f(C) = 2 + 7 = 9

Current State = CCurrent State = C

f(B) = 1 + 6 = 7f(B) = 1 + 6 = 7

f(H) = f(H) = Current State = BCurrent State = B

f(S) = 2 + 8 = 10f(S) = 2 + 8 = 10

f(A) = 4 + 5 = 9f(A) = 4 + 5 = 9

f(E) = 4 + 2 = 6f(E) = 4 + 2 = 6

f(C) = f(C) =

Current State = ECurrent State = E

f(B) = 4 + 9 = 13f(B) = 4 + 9 = 13

f(D) = 3 + 2 = 5f(D) = 3 + 2 = 5

f(F) = 1 + 1 = 2f(F) = 1 + 1 = 2

A B

C

S

(4)

(4) D

(5)

2

(2)

G

(1)

E

(2)H

(0)

34

41

(5)

F

2 13

2

Another Example

Page 21: AND/OR graphs

A B

C

S

(4)

(4) D

(5)

2

(2)

G

(1)

E

(2)H

(0)

34

41

(5)

F

2 13

2

Current State = FCurrent State = F

f(E) = 1 + 5 = 6 f(E) = 1 + 5 = 6

Current State = ECurrent State = E

f(D) = 3 + 2 = 5f(D) = 3 + 2 = 5

f(B) = 4 + 9 = 13f(B) = 4 + 9 = 13

f(F) = f(F) = Current State = DCurrent State = D

f(G) = 2 + 0 = 2f(G) = 2 + 0 = 2

f(E) = 3 + 13 = 16f(E) = 3 + 13 = 16

Visited Nodes =Visited Nodes =

S, B, C, H, C, B, E, F, E, D, GS, B, C, H, C, B, E, F, E, D, G

Path = S, B, E, D, GPath = S, B, E, D, G

Another Example