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Questions and Answers
What is the order in which operations are computed called?
What is the result of the expression 1 + 3 * 4?
Which operators have a higher precedence than + and -?
How can the order of evaluation be forced in an expression?
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What is the purpose of the ** operator in an expression?
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What is the result of the expression 2 * 3 + 4?
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What is the primary goal of Uniform Cost Search?
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What is the purpose of the helper function 'Path cost' in Uniform Cost Search?
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In what order are elements popped from the priority queue in Uniform Cost Search?
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What is the criterion used to break ties in Uniform Cost Search?
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What is the main difference between Uniform Cost Search and Breadth-First Search?
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When should Uniform Cost Search be used?
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What is the main characteristic of Uniform Cost Search?
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What is the role of the priority queue in Uniform Cost Search?
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How is the total cost of a path calculated in Uniform Cost Search?
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What is the advantage of using Uniform Cost Search over Breadth-First Search?
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Study Notes
Relational Operators
- Many logical expressions use relational operators.
Logical Operators
- These operators return true or false.
Indentation in Python
- Python provides no braces to indicate blocks of code for class and function definitions or flow control.
Basic Operators
- Arithmetic operators used in Python:
- Addition, subtraction/negation: +
- Multiplication: *
- Division: /
- Modulus (remainder): %
- Exponentiation: **
- Precedence of operators:
- *, /, %, ** have higher precedence than +, -
- Use of parentheses:
- Can be used to force a certain order of evaluation.
- Example calculation:
- 1 + 3 * 4 is 13
Intelligent Agents
- Intelligent agents are a type of artificial intelligence that can perceive their environment and take actions to achieve a goal.
State Representation
- No notes provided for this topic.
Problem Formulation
- No notes provided for this topic.
Solving Problems By Search
- No notes provided for this topic.
Search Strategies
-
Breadth-First Search (BFS)
- Properties:
- Completeness: Yes, if b is finite, a solution will be found if exists.
- Time Complexity: bd+1 (nodes until the solution)
- Space Complexity: bd+1 (keeps every generated node in memory)
- Optimality: Yes, if cost = 1 per step
- Not suitable for searching large graphs due to high time and space complexity.
- Properties:
-
Uniform-Cost Search (UCS)
- Visits the next node which has the least total cost from the root, until a goal state is reached.
- Similar to BFS, but with an evaluation of the cost for each reachable node.
- g(n) = path cost(n) = sum of individual edge costs to reach the current node.
- Properties:
- Completeness: Yes, if b is finite, and step cost is positive.
- Time Complexity: much larger than bd, and just bd if all steps have the same cost.
- Space Complexity: as above.
- Optimality: Yes.
- Requires that the goal test being applied when a node is removed from the nodes list rather than when the node is first generated while its parent node is expanded.
- Use a priority queue (least cost first) and pop the element with least cost.
- If two elements have the same cost, use alphabetic order.
- Depth-First Search (DFS) and Depth-Limited Search are not detailed in this text.
- Iterative Deepening is not detailed in this text.
Uniform Cost Search
- Use a priority queue (least cost first) and pop the element with least cost.
- If two elements have the same cost, use alphabetic order.
- Helper function: Path cost calculates the total cost of a path.
Summary
- Breadth-First Search (BFS) and Depth-First Search (DFS) are the foundation for all other search techniques.
- Uniform-Cost Search is used when actions have varying costs and the least cost solution is required.
- This is the only uninformed search that worries about costs.
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Description
This quiz covers basic operators and syntax in Python, including relational operators, logical operators, and indentation rules.
