AI Fundamentals Quiz for Competitive Exams

Study Notes

Preparing questions from the basics of Artificial Intelligence (AI) for Book Chordi, covering chapters 2, 3, 4, and 9.

A fundamental concept in AI, CSP involves finding a solution that satisfies a set of constraints or rules
CSP is a type of problem-solving approach used in AI to identify solutions that meet specific requirements
Key applications of CSP include:
- Resource allocation
- Scheduling
- Planning
- Configuration
CSP is a vital component of many AI systems, including:
- Expert Systems
- Decision Support Systems
- Natural Language Processing (NLP)
- Robotics

CSPs typically involve a set of variables and a set of constraints
Each variable has a specific domain or range of possible values
Constraints define the rules or restrictions that must be satisfied by the solution
CSPs can be classified into different types, including:
- Binary CSPs (involving two variables)
- N-ary CSPs (involving more than two variables)
- Hybrid CSPs (combining different types of constraints)

CSPs can be solved using various techniques, including:
- Brute Force Search
- Backtracking
- Forward Checking
- Constraint Propagation
- Local Search
Each technique has its own strengths and weaknesses, and the choice of technique depends on the specific problem and its characteristics