Lec 3 Search - PradiptaBiswas · 2019. 9. 16. · Microsoft PowerPoint - Lec 3 Search.pptx Author:...
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19-01-2018 1 Dr Pradipta Biswas, PhD (Cantab) Assistant Professor Indian Institute of Science http://cpdm.iisc.ernet.in/PBiswas.htm 2 • STATE-SPACE SEARCH • STATES • STATE-SPACE • OPTIMAL START STATE GOAL STATE • • • • • • • • • • • •
Transcript of Lec 3 Search - PradiptaBiswas · 2019. 9. 16. · Microsoft PowerPoint - Lec 3 Search.pptx Author:...
19-01-2018
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Dr Pradipta Biswas, PhD (Cantab)Assistant Professor
Indian Institute of Sciencehttp://cpdm.iisc.ernet.in/PBiswas.htm
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• STATE-SPACE SEARCH
• STATES
• STATE-SPACE
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OPTIMAL
START STATE GOAL STATE
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• UNINFORMED (BLIND):
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• VARIOUS BLIND STRATEGIES:
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• INSERTED
Initial state = AIs A a goal state?
Put A at end of queue.frontier = [A]
Future= green dotted circlesFrontier=white nodesExpanded/active=gray nodesForgotten/reclaimed= black nodes
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Expand A to B, C. Is B or C a goal state?
Put B, C at end of queue.frontier = [B,C]
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Expand B to D, EIs D or E a goal state?
Put D, E at end of queuefrontier=[C,D,E]
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Expand C to F, G.Is F or G a goal state?
Put F, G at end of queue.frontier = [D,E,F,G]
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Expand D to no children.Forget D.
frontier = [E,F,G]
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Expand E to no children.Forget B,E.
frontier = [F,G]
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• COMPLETE?
• TIME?
• SPACE?
• OPTIMAL?
• F(D) ≥ F(D-1),
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• SPACE
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• INSERTED
Initial state = AIs A a goal state?
Put A at front of queue.frontier = [A]
Future= green dotted circlesFrontier=white nodesExpanded/active=gray nodesForgotten/reclaimed= black nodes
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Expand A to B, C. Is B or C a goal state?
Put B, C at front of queue.frontier = [B,C]
Future= green dotted circlesFrontier=white nodesExpanded/active=gray nodesForgotten/reclaimed= black nodes
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Expand B to D, E. Is D or E a goal state?
Put D, E at front of queue.frontier = [D,E,C]
Future= green dotted circlesFrontier=white nodesExpanded/active=gray nodesForgotten/reclaimed= black nodes
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Expand D to H, I. Is H or I a goal state?
Put H, I at front of queue.frontier = [H,I,E,C]
Future= green dotted circlesFrontier=white nodesExpanded/active=gray nodesForgotten/reclaimed= black nodes
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Expand H to no children.Forget H.
frontier = [I,E,C]
Future= green dotted circlesFrontier=white nodesExpanded/active=gray nodesForgotten/reclaimed= black nodes
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Expand I to no children.Forget D, I.
frontier = [E,C]
Future= green dotted circlesFrontier=white nodesExpanded/active=gray nodesForgotten/reclaimed= black nodes
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Expand E to J, K. Is J or K a goal state?
Put J, K at front of queue.frontier = [J,K,C]
Future= green dotted circlesFrontier=white nodesExpanded/active=gray nodesForgotten/reclaimed= black nodes
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Expand I to no children.Forget D, I.
frontier = [E,C]
Future= green dotted circlesFrontier=white nodesExpanded/active=gray nodesForgotten/reclaimed= black nodes
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Expand K to no children.Forget B, E, K.
frontier = [C]
Future= green dotted circlesFrontier=white nodesExpanded/active=gray nodesForgotten/reclaimed= black nodes
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Expand C to F, G. Is F or G a goal state?
Put F, G at front of queue.frontier = [F,G]
Future= green dotted circlesFrontier=white nodesExpanded/active=gray nodesForgotten/reclaimed= black nodes
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• COMPLETE?
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• TIME?
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• SPACE?
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• OPTIMAL?
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• To avoid the infinite depth problem of DFS,
only search until depth L,
i.e., we don’t expand nodes beyond depth L.� Depth-Limited Search
• What if solution is deeper than L? � Increase L iteratively.
� Iterative Deepening Search
• This inherits the memory advantage of Depth-first search
• Better in terms of space complexity than Breadth-first search.
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INFORMED SEARCH STRATEGIES
• SELECT WHICH NODE TO EXPAND NEXT DURING SEARCH
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• W(N)
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• APPEARS
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� COMPLETE?
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� TIME?
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� SPACE?
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� OPTIMAL?
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• GENERALLY THE PREFERRED SIMPLE HEURISTIC SEARCH
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• ESTIMATE
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ESTIMATE
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S i
S
S f
g(S)
h(S)
f(S)
Components of A*
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• COMPLETE?
• TIME/SPACE?
• OPTIMAL?
• OPTIMALLY EFFICIENT?
* *| ( ) ( ) | (log ( ))h n h n O h n− ≤
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P. Biswas, Interactive Gaze Controlled Projected Display, Patent Application No.: 201641037828
• STATE SPACE
• STATES
• START STATE
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• GOAL STATES
• OPERATORS
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Each set of colored dots represents a state
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•0.95
1.66
1.13
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Projected_HS Projected Touch
MEA
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IATI
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Mean Deviation from Lane
2608.723030.29
2556.72
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Projected_HS Projected Touch
RESP
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SE T
IME (
IN M
SEC
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Response Time
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TAKE AWAY POINTS
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![Lec-3 [41]](https://static.fdocuments.in/doc/165x107/577ce3b31a28abf1038ccaf9/lec-3-41.jpg)
