For Friday Read chapter 4, sections 1 and 2 Homework –Chapter 3, exercise 7 –May be done in...
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Transcript of For Friday Read chapter 4, sections 1 and 2 Homework –Chapter 3, exercise 7 –May be done in...
![Page 1: For Friday Read chapter 4, sections 1 and 2 Homework –Chapter 3, exercise 7 –May be done in groups.](https://reader036.fdocuments.in/reader036/viewer/2022082713/5697bf951a28abf838c90831/html5/thumbnails/1.jpg)
For Friday
• Read chapter 4, sections 1 and 2
• Homework– Chapter 3, exercise 7– May be done in groups
![Page 2: For Friday Read chapter 4, sections 1 and 2 Homework –Chapter 3, exercise 7 –May be done in groups.](https://reader036.fdocuments.in/reader036/viewer/2022082713/5697bf951a28abf838c90831/html5/thumbnails/2.jpg)
Homework Review
• Reflex actions
• Programming
• Genes
• Laws of physics (determinism)
![Page 3: For Friday Read chapter 4, sections 1 and 2 Homework –Chapter 3, exercise 7 –May be done in groups.](https://reader036.fdocuments.in/reader036/viewer/2022082713/5697bf951a28abf838c90831/html5/thumbnails/3.jpg)
Pathfinding
![Page 4: For Friday Read chapter 4, sections 1 and 2 Homework –Chapter 3, exercise 7 –May be done in groups.](https://reader036.fdocuments.in/reader036/viewer/2022082713/5697bf951a28abf838c90831/html5/thumbnails/4.jpg)
Solving Problems
• Getting from the current state of the world to the state we want the world to be in.
• May or may not matter how we get there.
![Page 5: For Friday Read chapter 4, sections 1 and 2 Homework –Chapter 3, exercise 7 –May be done in groups.](https://reader036.fdocuments.in/reader036/viewer/2022082713/5697bf951a28abf838c90831/html5/thumbnails/5.jpg)
Problem Formulation
• Initial state
• Goal state
• Operators that change the state of the world
• Path cost – for when it matters how we get there
![Page 6: For Friday Read chapter 4, sections 1 and 2 Homework –Chapter 3, exercise 7 –May be done in groups.](https://reader036.fdocuments.in/reader036/viewer/2022082713/5697bf951a28abf838c90831/html5/thumbnails/6.jpg)
Toy Problems
• 8-puzzle
• N-queens
• Peg puzzle
• Farmer, wolf, goat and cabbage
• Missionaries and cannibals
![Page 7: For Friday Read chapter 4, sections 1 and 2 Homework –Chapter 3, exercise 7 –May be done in groups.](https://reader036.fdocuments.in/reader036/viewer/2022082713/5697bf951a28abf838c90831/html5/thumbnails/7.jpg)
More Realistic Problems
• Route finding
• Traveling Salesman Problem
• VLSI layout
• Robot navigation
• Web searching
![Page 8: For Friday Read chapter 4, sections 1 and 2 Homework –Chapter 3, exercise 7 –May be done in groups.](https://reader036.fdocuments.in/reader036/viewer/2022082713/5697bf951a28abf838c90831/html5/thumbnails/8.jpg)
Searching Concepts
• A state can be expanded by generating all states that can be reached by applying a legal operator to the state
• State space can also be defined by a successor function that returns all states produced by applying a single legal operator
• A search tree is generated by generating search nodes by successively expanding states starting from the initial state as the root
![Page 9: For Friday Read chapter 4, sections 1 and 2 Homework –Chapter 3, exercise 7 –May be done in groups.](https://reader036.fdocuments.in/reader036/viewer/2022082713/5697bf951a28abf838c90831/html5/thumbnails/9.jpg)
Search Node Contents
• May include– Corresponding state– Parent node– Operator applied to reach this node– Length of path from root to node (depth)– Path cost of path from initial state to node
![Page 10: For Friday Read chapter 4, sections 1 and 2 Homework –Chapter 3, exercise 7 –May be done in groups.](https://reader036.fdocuments.in/reader036/viewer/2022082713/5697bf951a28abf838c90831/html5/thumbnails/10.jpg)
General Search Function
function General-Search(problem, strategy)
returns a solution, or failure
initialize the search tree using the initial state of problem
loop do
if there are no candidates for expansion then
return failure
choose a leaf node for expansion according to strategy
if the node contains a goal state then
return the corresponding solution
else
expand the node and add the resulting nodes to the search tree
end loop
end
![Page 11: For Friday Read chapter 4, sections 1 and 2 Homework –Chapter 3, exercise 7 –May be done in groups.](https://reader036.fdocuments.in/reader036/viewer/2022082713/5697bf951a28abf838c90831/html5/thumbnails/11.jpg)
Implementing Search Algorithms
• Maintain a list of unexpanded search nodes
• By using different strategies for ordering the list of search nodes, we implement different searching strategies
• Eg. breadth-first search is implemented using a queue and depth-first using a stack (as we’ll see soon)
![Page 12: For Friday Read chapter 4, sections 1 and 2 Homework –Chapter 3, exercise 7 –May be done in groups.](https://reader036.fdocuments.in/reader036/viewer/2022082713/5697bf951a28abf838c90831/html5/thumbnails/12.jpg)
Search Function Revisited
function General-Search(problem, Queuing-Fn)
returns a solution, or failure
nodes <- MakeQueue(Make-Node(Initial-State(problem)))
loop do
if nodes is empty then
return failure
node <- Remove-Front(nodes)
if Goal-Test(problem) applied to State(node) succeeds then
return the corresponding solution
else
nodes <- Queuing-Fn(nodes, Expand(node, Operators(problem)))
end loop
end
![Page 13: For Friday Read chapter 4, sections 1 and 2 Homework –Chapter 3, exercise 7 –May be done in groups.](https://reader036.fdocuments.in/reader036/viewer/2022082713/5697bf951a28abf838c90831/html5/thumbnails/13.jpg)
Properties of Search Strategies
• Completeness
• Time Complexity
• Space Complexity
• Optimality
![Page 14: For Friday Read chapter 4, sections 1 and 2 Homework –Chapter 3, exercise 7 –May be done in groups.](https://reader036.fdocuments.in/reader036/viewer/2022082713/5697bf951a28abf838c90831/html5/thumbnails/14.jpg)
Two Types of Search• Uninformed Search
– Also called blind, exhaustive or brute-force– Make use of no information about the problem– May be quite inefficient
• Informed Search– Also called heuristic or intelligent– Uses information about the problem to guide the search– Usually guesses the distance to a goal state– Not always possible
![Page 15: For Friday Read chapter 4, sections 1 and 2 Homework –Chapter 3, exercise 7 –May be done in groups.](https://reader036.fdocuments.in/reader036/viewer/2022082713/5697bf951a28abf838c90831/html5/thumbnails/15.jpg)
Breadth-First Search
• List ordering is a queue
• All nodes at a particular depth are expanded before any below them
• How does BFS perform?– Completeness– Optimality
![Page 16: For Friday Read chapter 4, sections 1 and 2 Homework –Chapter 3, exercise 7 –May be done in groups.](https://reader036.fdocuments.in/reader036/viewer/2022082713/5697bf951a28abf838c90831/html5/thumbnails/16.jpg)
Complexity of BFS
• Branching Factor• For branching factor b and solution at depth d in
the tree (i.e. the path-length of the solution is d)– Time required is: 1 + b + b2 + b3 + … bd
– Space required is at least bd
• May be highly impractical• Note that ALL of the uninformed search
strategies require exponential time
![Page 17: For Friday Read chapter 4, sections 1 and 2 Homework –Chapter 3, exercise 7 –May be done in groups.](https://reader036.fdocuments.in/reader036/viewer/2022082713/5697bf951a28abf838c90831/html5/thumbnails/17.jpg)
Uniform Cost Search
• Similar to breadth first, but takes path cost into account
![Page 18: For Friday Read chapter 4, sections 1 and 2 Homework –Chapter 3, exercise 7 –May be done in groups.](https://reader036.fdocuments.in/reader036/viewer/2022082713/5697bf951a28abf838c90831/html5/thumbnails/18.jpg)
Depth First Search
• How does depth first search operate?
• How would we implement it?
• Performance:– Completeness– Optimality– Space Complexity– Time Complexity
![Page 19: For Friday Read chapter 4, sections 1 and 2 Homework –Chapter 3, exercise 7 –May be done in groups.](https://reader036.fdocuments.in/reader036/viewer/2022082713/5697bf951a28abf838c90831/html5/thumbnails/19.jpg)
Comparing DFS and BFS
• When might we prefer DFS?
• When might we prefer BFS?