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Artificial Intelligence Course outline Introduction Problem solving Generic algorithms Knowledge Representation and Reasoning Expert Systems Uncertainty.

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Presentation on theme: "Artificial Intelligence Course outline Introduction Problem solving Generic algorithms Knowledge Representation and Reasoning Expert Systems Uncertainty."— Presentation transcript:

1 Artificial Intelligence Course outline Introduction Problem solving Generic algorithms Knowledge Representation and Reasoning Expert Systems Uncertainty Learning Planning Advanced topics in AI CIIT Sahiwal

2 Artificial Intelligence Problem Solving and Search Muhammad Ejaz CIIT Sahiwal

3 Problem Solving The mechanism to find the goal performing some actions to transit from one state to another is known as problem solving. Initial state Operator: description of an action State space: all states reachable from the initial state by any sequence action Path: sequence of actions leading from one state to another Goal test: which the agent can apply to a single state description to determine if it is a goal state Path cost function: assign a cost to a path which the sum of the costs of the individual actions along the path. CIIT Sahiwal

4 Different types of problem Well structured problems  When problem description and its rules are described clearly and unambiguously. Ill structured problem  No extra information about the problem other than the definition No extra information No heuristics (rules) CIIT Sahiwal

5 Well Defined Problems Finding the maximum from a sequence of integers. Eight puzzle 1,2 or 2,1 puzzle Farmer and goose problem Water pouring problem CIIT Sahiwal

6 Eight puzzle CIIT Sahiwal

7 Water Pouring Problem CIIT Sahiwal

8 Farmer and goose problem W F ~ W F G F W F G ~ G F ~ W C W C C ~ G F G ~ C F ~ W C F ~ C F W W G ~ G G ~ G C C C F C W ~ G W CIIT Sahiwal

9 Think Point What will be tree representation of Farmer and goose problem? CIIT Sahiwal

10 Searching For Solutions Having formulated some problems…how do we solve them? Search through a state space Use a search tree that is generated with an initial state and successor functions that define the state space CIIT Sahiwal

11 Different search techniques Uninformed Search  Only the information available in the problem definition – Also known as blind searching -Breadth-first search -Depth-first search -Depth-limited search -Iterative deepening search Informed Search  When sufficient information is provided to reach the goal. CIIT Sahiwal

12 Breadth-First Search Recall from Data Structures the basic algorithm for a breadth-first search on a graph or tree Expand the shallowest unexpanded node Place all new successors at the end of a FIFO queue CIIT Sahiwal

13 Breadth-First Search CIIT Sahiwal

14 Breadth-First Search CIIT Sahiwal

15 Breadth-First Search CIIT Sahiwal

16 Breadth-First Search CIIT Sahiwal

17 Depth-First Search Recall from Data Structures the basic algorithm for a depth-first search on a graph or tree Expand the deepest unexpanded node Unexplored successors are placed on a stack until fully explored CIIT Sahiwal

18 Depth-First Search CIIT Sahiwal

19 Depth-First Search CIIT Sahiwal

20 Depth-First Search CIIT Sahiwal

21 Depth-First Search CIIT Sahiwal

22 Depth-First Search CIIT Sahiwal

23 Depth-First Search CIIT Sahiwal

24 Depth-First Search CIIT Sahiwal

25 Depth-First Search CIIT Sahiwal

26 Depth-First Search CIIT Sahiwal

27 Depth-First Search CIIT Sahiwal

28 Depth-First Search CIIT Sahiwal

29 Depth-First Search CIIT Sahiwal


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