Penentuan Rute RoutePath Planning Bagian 1 BFS DFS

Penentuan Rute (Route/Path Planning) Bagian 1: BFS, DFS, UCS, Greedy Best First Search Bahan Kuliah IF 2211 Strategi Algoritma Oleh: Nur Ulfa Maulidevi Program Studi Teknik Informatika Sekolah Teknik Elektro dan Informatika ITB 2021

Referensi 1. Materi kuliah IF 3170 Inteligensi Buatan Teknik Informatika ITB, Course Website: http: //kuliah. itb. ac. id STEI Teknik Informatika IF 3170 2. Stuart J Russell & Peter Norvig, Artificial Intelligence: A Modern Approach, 3 rd Edition, Prentice-Hall International, Inc, 2010, Textbook Site: http: //aima. cs. berkeley. edu/ (2 nd edition) 3. Free online course materials | MIT Open. Course. Ware Website: Site: http: //ocw. mit. edu/courses/electrical-engineering-andcomputer-science/ 4. Lecture Notes in Informed Heuristic Search, ICS 271 Fall 2008, http: //www. ics. uci. edu/~dechter/courses/ics-271/fall-08/lecturenotes/4. Informed. Heuristic. Search. ppt IF 2211/NUM/29 Mar 2016 2

Route Planning IF 2211/NUM/29 Mar 2016 3

Source: Russell’s book Search O 71 151 Z S 99 F 211 75 A 80 140 R 120 118 T 111 L 70 M 75 97 B P 101 D 146 138 C (a part of graph of Romania) IF 2211/NUM/29 Mar 2016 S: set of cities i. s: A (Arad) g. s: B (Bucharest) Goal test: s = B ? Path cost: time ~ distance 5

Blind Search Uninformed Search • • • BFS (Breadth First Search) DFS (Depth First Search) DLS (Depth Limited Search) IDS (Iterative Deepening Search) UCS (Uniform Cost Search) IF 2211/NUM/29 Mar 2016 6

Breadth-First Search (BFS) Z Treat agenda as a queue (FIFO) Z O 71 S 151 S O F 99 211 75 A 80 140 R 120 118 T 111 L 70 M 75 P 97 D 101 B 138 146 A Pohon BFS C Path: A S F B, Path-cost = 450 IF 2211/NUM/29 Mar 2016 Queue O F Goal B Simpul-E T R C L P M Simpul Hidup A ZA, SA, TA ZA SA, TA, OAZ SA TA, OAZ, OAS, FAS, RAS TA OAZ, OAS, FAS, RAS, LAT OAZ OAS, FAS, RAS, LAT OAS FAS, RAS, LAT FAS RAS, LAT, BASF RAS LAT, BASF, DASR, CASR, PASR LAT BASF, DASR, CASR, PASR, MATL BASF Solusi ketemu 7

Depth-First Search (DFS) Treat agenda as a stack (LIFO) Z A O 71 S 151 A Pohon DFS S Z F 99 T O 211 75 80 140 S R 120 118 T 111 L 70 M 75 97 B P 101 D 146 138 C Path: A Z O S F B Path-cost = 607 IF 2211/NUM/29 Mar 2016 F B R Stack Goal Simpul-E Simpul Hidup A ZA, SA, TA ZA OAZ, SA, TA OAZ SAZO, SA, TA SAZO FAZOS, RAZOS, SA, TA FAZOS BAZOSF, RAZOS, SA, TA BAZOSF 8 Solusi ketemu

Iterative Deepening Search (IDS) Z O 151 71 S Z 211 80 140 R 120 118 T 111 L 70 M 75 97 B P 101 D 146 Depth 0 A F 99 75 A Pohon IDS O S 1 T F R B Goal 2 L 3 138 C Depth=0: A: cutoff Depth=1: A ZA, SA, TA ZA: cutoff, SA: cutoff, TA: cutoff Depth=2: A ZA, SA, TA OAZ : cutoff FAS, RAS, TA FAS : cutoff RAS : cutoff LAT : cutoff Depth=3: A ZA, SA, TA OAZ, SA, TA SAZO: cutoff FAS, RAS, TA BASF IF 2211/NUM/29 Mar 2016 9

Simpul-E Uniform Cost Search (UCS) • BFS & IDS find path with fewest steps (A-S-F-B) • If steps ≠ cost, this is not relevant (to optimal solution) • How can we find the shortest path (measured by sum of distances along path)? • g(n) = path cost from root to n Z O 71 S 151 F 99 211 75 A 80 140 R 97 120 118 T 111 L 70 M 75 B P 146 ZA-75, TA-118, SA-140 ZA-75 TA-118, SA-140, OAZ-146 TA-118 SA-140, OAZ-146, LAT-229 SA-140 OAZ-146, RAS-220, LAT-229, FAS-239, OAS-291 OAZ-146 RAS-220, LAT-229, FAS-239, OAS-291 RAS-220 LAT-229, FAS-239, OAS-291, PASR-317, DASR-340, CASR-366 LAT-229 FAS-239, OAS-291, MATL-299, PASR-317, DASR-340, CASR-366 FAS-239 OAS-291, MATL-299, PASR-317, DASR-340, CASR-366, BASF-450 OAS-291 MATL-299, PASR-317, DASR-340, CASR-366, BASF-450 MATL-299 PASR-317, DASR-340, DATLM-364, CASR-366, BASF-450 PASR-317 DASR-340, DATLM-364, CASR-366, BASRP-418, CASRP-455, BASF 450 101 D A Simpul Hidup 138 DASR-340 DATLM-364, CASR-366, BASRP-418, CASRP-455, BASF-450 DATLM-364 CASR-366, BASRP-418, CASRP-455, BASF-450 CASR-366 BASRP-418, CASRP-455, BASF-450 B Solusi ketemu C Path: A S R P B Path-cost = 418 optimal solution IF 2211/NUM/29 Mar 2016 10

Heuristic Search Informed Search • • Greedy Best First Search A* IF 2211/NUM/29 Mar 2016 11

Greedy Best-First Search • Idea: use an evaluation function f(n) for each node • f(n) = h(n) estimates of cost from n to goal • e. g. , h. SLD(n) = straight-line distance from n to Bucharest • Greedy best-first search expands the node that appears to be closest to goal Romania with step costs in km: IF 2211/NUM/29 Mar 2016 12

Greedy best-first search example IF 2211/NUM/29 Mar 2016 13

Greedy best-first search example IF 2211/NUM/29 Mar 2016 14

Greedy best-first search example IF 2211/NUM/29 Mar 2016 15

Greedy best-first search example Path: Arad Sibiu Fagaras Bucharest, Path -cost = 450 not optimal solution IF 2211/NUM/29 Mar 2016 16

Problems with Greedy Best First Search 1. Not complete Lasi to Fragaras?

Problems with Greedy Best First Search 2. Get stuck with local minima/plateu 3. Irrevocable (not able to be reversed/changed) 4. Can we incorporate heuristics in systematic search? IF 2211/NUM/29 Mar 2016 18

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