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State space search and Problem Solving techniques
The document discusses artificial intelligence problem spaces and state space representation, outlining key concepts such as defining the problem, analyzing it, and selecting appropriate problem-solving techniques. It explains uninformed (blind) and informed (heuristic) search techniques, highlighting their differences in complexity, optimality, and methods like breadth-first and A* search. Additionally, it lists various AI problems related to games, routing, layout, assembly sequencing, and task scheduling.
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Introduction to Artificial Intelligence and an overview of problem spaces, state spaces, and searching techniques.
Explains the components of defining a problem space including problem definition, analysis, task knowledge, and solving techniques.
Describes state space as a representation of problems using graph models with states as nodes and operators as edges.
Illustrates the problem space specifically for the 8 puzzle example.
Outlines search strategy metrics: completeness, time complexity, space complexity, and optimality in the context of state space.
Introduces two primary searching techniques: Uninformed/Blind search and Informed/Heuristic search.
Details uninformed search techniques like BFS and DFS, their characteristics, complexities, and examples.
Describes informed search techniques using heuristics, their advantages, speed of finding solutions, and complexity.
Lists various AI problems, including games, route finding, and scheduling, highlighting areas where AI is applied.
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State space search and Problem Solving techniques
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- 2. ◊ Problem Spaces. ◊State Space. ◊ Searching Techniques. ◊ Uninformed search technique. ◊ Informed search techniques. ◊ Some AI problems. In This Video
- 3. Problem Space Define theproblem in detail is known as problem space. There are 4 things concerned to solve a particular problem. Define the problem precisely. Analyze the problem. Isolate and represent the task knowledge i.e. required to solve the problem. Selection of the best problem solving technique and apply it. Like Tower of Hanoi, 8 puzzle games.
- 4. Set ofstates and the connections between them to represent the problem. Graph is used represent problem. States are represented by nodes of the graph, and the operators by edges between nodes. For simplicity it is represented as trees, where the initial state is the root of the tree. State Space
- 5. S:{S,A,Action(s),Result(s,a),Cost(s,a)} Where, S: set ofstates like start state, goal state, etc. A :set of actions available. s: an individual state from S. Action(s): action performed on s . a: any action from set A. Result(s, a): An intermediate state obtain by performing a on s. Cost(s, a):cost of executing action a on s. branching factor, should be minimum. State Space Search
- 6. Problem Space of8 puzzle
- 7. Search Strategy A strategyis defined by picking the order of node expansion. Completeness- does it always find a solution if one exists? Time complexity- no. of nodes generated. Space complexity- max no. of nodes in memory. Optimality- does it always find least cost solution? Time and space is measured in ‘b’ – max branching factor of search tree. ‘d’- depth of least cost solution. ‘m’ – max depth of the state space may be (infinite)
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- 9. Uninformed Search Alsoknown as Blind search. Problems require no domain specific knowledge. No idea, how to obtain solution, we apply Brute force technique (explore every possible step). Time consuming. Time/Space Complexity is more. For e.g., Travelling salesman problem for 5 cities needs (n-1)! Search. Non polynomial method. Provides optimal solution. Methods: Breath first search (BFS), Depth first search(DFS)
- 10. Informed Search • Alsoknown as Heuristic search(estimation). • Search with information. • Heuristic function is used to find steps of the solution. • Provides quick solution. • Less Time and space complexity. • Does not produce optimal solution. • Perform search in exponential time. • Methods: A*, Heuristic DFS, Best first search.
- 11. AI PROBLEMS • Games:WaterJug problem ,8 Queen problem, 8 Puzzle problem • Missionaries and Cannibals ,The Monday & Bananas problem. • Route finding.(computer networks, airline travel planning system) • Layout problems (VLSI layout, furniture layout, packaging) • Assembly sequencing.(Assembly of electrical motors) • Task Scheduling.(Time tables, manufacturing)