PROBLEM SOLVING IN ARTIFICIAL INTELLIGENCE -

informed search, adversarial search (game playing), knowledge representation

This course is not sponsored by or affiliated with Udemy, Inc.”

This course introduces the core concepts, techniques, and strategies used in Artificial Intelligence (AI) to solve complex problems. Designed for beginners and intermediate learners. it focuses on enabling systems to make decisions, solve complex problems, and act intelligently in dynamic environments.

Learners will be able to analyze problems, select appropriate AI techniques, and implement solutions. Students will explore classical AI approaches such as search algorithms, constraint satisfaction, and planning.

Learning Outcomes:

By the end of this course, students will be able to:

• Formulate real-world scenarios as AI problem-solving tasks.

• Implement and compare various search and planning algorithms.

• Solve constraint satisfaction problems using AI techniques.

• Design agents that can make decisions in adversarial environments.

• Apply AI problem-solving methods in domains such as games and navigation.

Topics Covered:

• Introduction to Problem solving with AI

• AI Techniques, Problem solving process

• Problem types and characteristics, Problem space and search

• TOY Problem

• Searching for solutions

• Informed Search Methods (Best First search, A* Algorithm)

• Adversarial Search Methods (Game Theory) (Minmax and Alpha Beta Pruning)

• Constraint satisfactory problems (Crypt Arithmetic Problems)

• AI Agents

• Knowledge Representation in AI - Wumpus World problem

• Unification and Resolution

• Planning - Blocks World Problem