heuristic search

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Heuristic search heuristic search attempts to find the best tree, without looking at all possible trees

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Heuristic search. heuristic search attempts to find the best tree, without looking at all possible trees. heuristic search methods tend to be greedy. heuristic search methods may fail to find the best solution. global optimum. local optimum. Moving through the trees. - PowerPoint PPT Presentation

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Page 1: Heuristic search

Heuristic searchheuristic search attempts to find the best tree, without looking at all possible trees

Page 2: Heuristic search

heuristic search methods tend to be greedy

Page 3: Heuristic search
Page 4: Heuristic search

local optimumglobal optimum

heuristic search methods may fail to find the best solution

Page 5: Heuristic search

Moving through the trees

1. Nearest-neighbour interchanges

ba c

ed

nearest neighbour interchanges ‘swap’ adjacent branches to find alternative trees

Page 6: Heuristic search

Moving through the trees

1. Nearest-neighbour interchanges

ba c

ed

nearest neighbour interchanges starts by erasing an internal branch

Page 7: Heuristic search

Moving through the forest

1. Nearest-neighbour interchanges

ba c

ed

and then erases the two braches connected to it at each end

Page 8: Heuristic search

Moving through the forest

1. Nearest-neighbour interchanges

ba c

edb

e a

cd

the four subtrees are now hooked together in all possible ways

((a+c) + e) + (b+d)

Page 9: Heuristic search

Moving through the forest

1. Nearest-neighbour interchanges

ba c

edb

e a

cd

bc a

ed

((a+e) + c) + (b+d)

Page 10: Heuristic search

Moving through the forest

1. Nearest-neighbour interchanges

ba c

edb

e a

cd

bc a

ed

ba c

ed

now a second internal branch is erased and the procedure is repeated

Page 11: Heuristic search

Moving through the forest

1. Nearest-neighbour interchanges

ba c

edb

e a

cd

bc a

ed

ba c

eda

b c

ed

bd c

ea

Page 12: Heuristic search

Moving through the forest

1. Nearest-neighbour interchanges

ba c

edb

e a

cd

bc a

ed

ba c

eda

b c

ed

bd c

ea

Page 13: Heuristic search

b d c

ea

a b c

ed

b c e

ad

a d b

ce

b a c

eda e b

dc

a b d

eca d b

ec

a c b

ed

a e b

cd

a e c

dbc a b

ed

a b c

de

d a b

ce

a c d

eb

Page 14: Heuristic search

Characters

Species 1 2 3 4 5 6

Alpha (a) 1 0 0 1 1 0

Beta (b) 0 0 1 0 0 0

Gamma (c) 1 1 0 0 0 0

Delta (d) 1 1 0 1 1 1

Epsilon (e) 0 0 1 1 1 0

Page 15: Heuristic search

b d c

ea

a b c

ed

b c e

ad

a d b

ce

b a c

eda e b

dc

a b d

eca d b

ec

a c b

ed

a e b

cd

a e c

dbc a b

ed

a b c

de

d a b

ce

a c d

eb

[11]

[11][11]

[11] [11]

[11]

[11][9]

[10] [10]

[9]

[9] [9]

[8]

[9]

Page 16: Heuristic search

b d c

ea

a b c

ed

b c e

ad

a d b

ce

b a c

eda e b

dc

a b d

eca d b

ec

a c b

ed

a e b

cd

a e c

dbc a b

ed

a b c

de

d a b

ce

a c d

eb

[11]

[11][11]

[11] [11]

[11]

[11][9]

[10] [10]

[9]

[9] [9]

[8]

[11]

[9]

Page 17: Heuristic search

b d c

ea

a b c

ed

b c e

ad

a d b

ce

b a c

eda e b

dc

a b d

eca d b

ec

a c b

ed

a e b

cd

a e c

dbc a b

ed

a b c

de

d a b

ce

a c d

eb

[11]

[11][11]

[11] [11]

[11]

[11][9]

[10] [10]

[9]

[9] [9]

[8]

[11]

[9]

Page 18: Heuristic search

b d c

ea

a b c

ed

b c e

ad

a d b

ce

b a c

eda e b

dc

a b d

eca d b

ec

a c b

ed

a e b

cd

a e c

dbc a b

ed

a b c

de

d a b

ce

a c d

eb

[11]

[11][11]

[11] [11]

[11]

[11][9]

[10] [10]

[9]

[9] [9]

[8]

[11]

[9]

Page 19: Heuristic search

b d c

ea

a b c

ed

b c e

ad

a d b

ce

b a c

eda e b

dc

a b d

eca d b

ec

a c b

ed

a e b

cd

a e c

dbc a b

ed

a b c

de

d a b

ce

a c d

eb

[11]

[11][11]

[11] [11]

[11]

[11][9]

[10] [10]

[9]

[9] [9]

[8]

[11]

[9]

Page 20: Heuristic search

Moving through the forest

1. Nearest-neighbour interchanges2. Subtree pruning and regrafting (SPR)

g c

a

df

b

i

hj

k

e

in SPR, a branch with a subtree is removed…

Page 21: Heuristic search

Moving through the forest

1. Nearest-neighbour interchanges2. Subtree pruning and regrafting

g c

a

d

fb

i

hj

k

e

… and reinserted in all possible places.

Page 22: Heuristic search

Moving through the forest

1. Nearest-neighbour interchanges2. Subtree pruning and regrafting

g c

a

d

fb

i

hj

k

e

Page 23: Heuristic search

Moving through the forest

1. Nearest-neighbour interchanges2. Subtree pruning and regrafting

g c

ad

fb

i

hj

k

e

Page 24: Heuristic search

Moving through the forest

1. Nearest-neighbour interchanges2. Subtree pruning and regrafting (SPR)3. Tree bisection and reconnection (TBR)

g c

a

df

b

i

hj

k

e

in TBR, the tree is first bisected …

Page 25: Heuristic search

Moving through the forest

1. Nearest-neighbour interchanges2. Subtree pruning and regrafting3. Tree bisection and reconnection

g c

a

df

b

i

hj

k

e

and then all possible connections are made between a branch of one subtree and a branch of the other

Page 26: Heuristic search

Moving through the forest

1. Nearest-neighbour interchanges2. Subtree pruning and regrafting3. Tree bisection and reconnection

g

c

a d

k

e

f

bi h

j

Page 27: Heuristic search

Moving through the forest

1. Nearest-neighbour interchanges2. Subtree pruning and regrafting3. Tree bisection and reconnection4. …

many more rearrangement methods exist and new ones are being developed

Page 28: Heuristic search

Sequential addition

a

b

c

the sequential addition strategy starts with a simple tree and adds species one by one

Page 29: Heuristic search

Sequential addition

a

b

c

a

b

c

d

a

d

b

c

a

c

b

d[9][7][8]

every new tree is evaluated on the way,...

Page 30: Heuristic search

Sequential addition

a

b

c

a

b

c

d

a

d

b

c

a

c

b

d

a

d

b

c

a

d

b

ea

d

c

e

a

e

b

c

e

d

b

c

a

d

ec

b

[9][9]

[9][9]

[11]

[9][7][8]

… and the most promising path is taken

Page 31: Heuristic search

Star decomposition

a

b c

d

e f

a

b c

d

e f

a

b cd

e f

a

b c

d

e f

star decomposition starts out with an unresolved tree and sequentially pairs species: e.g. UPGMA and neighbour-joining techniques