Artificial Intelligence

Reasoning, learning, searching for new information, extracting models from knowledge base systems and adapting to unpredictable situations are key fac- tors in any modern computer system. The goal of this course is to investigate knowledge representation models and algorithms that are useful to reason about facts and situations and are suitable to support advanced search and optimisation strategies other than learning systems. In fact, learning from ex- perience and from errors is a crucial aspect for any intelligent system that has to interact with an external environment. The course moves from simple to complex problems introducing concept such as heuristic search and approxi- mation algorithms. These are important tools to allow the student to theoreti- cally analyze and practically solve real life situations.

REFERENCES

• Artificial Intelligence: a modern approach. S. Russel and Peter Norvig. Prentice
  Hall, 1994

Course Material in Italian and English will be provided to the students

Additional readings:

• Artificial Intelligence, third edition, P.H. Winston, Addison-Wesley, 1992
• Genetic Algorithms in Search, Optimisation, and Machine Learning, Goldberg, Addison-Wesley, MA, 1989