Artificial Intelligence and laboratory

Module LABORATORY

Knowledge and understanding: Students will acquire basic knowledge about Intelligent Agents and their main features.
Applying knowledge and understanding: students will be to able to apply the acquired knowledge in several fields such as: searching for solutions to hard combinatorial problems, games and decision theory, automated deduction and reasoning.
Autonomia di giudizio (making judgements): Students will be able to evaluate the possibility of developing algorithms and intelligent systems to mechanize decisional processes in different application fields.
Communication skills: students will acquire the necessary communication skills and appropriate linguistic skills to explain and clarify problems relative to intelligent systems and their applications.
Capacità di apprendimento (learning skills): students will be able to adapt the acquire knowledge to new contexts as well and to understand the limits of applicability of artificial intelligence techniques

The course is divided into 2 main parts. First part on Problem Solving, and second part on Knowledge and Reasoning.

FIRST PART: Problem Solving

• Foundations and history of Artificial Intelligence
• Intelligent Agents and classifications
• Search and Problem Solving
• Search in games
• Constraint Satisfaction Problems
• Search using Natural Computing Algorithms

• SECOND PART: Knowledge, Reasoning and Learning

• Logical agents and puzzles
• First order logic and Inferences
• Uncertainty and Probability
• Decision making, Utility and value of information
• Learning from examples

Required textbook is Artificial Intelligence, a modern approach, 3^rd Edition, S. Russel, P. Norvig. Other material will be provided by the instructor in class.

1. Define and show an example of an admissible heuristics. 

2. Briefly describe algorithm Minimax

3. Briefly describe some heuristics for the Constraint Satisfaction Problem.