Welcome to the Computational Intelligence course! In this exciting journey, we'll delve into the fascinating world of intelligent systems, where machines learn, adapt, and make decisions based on data. Let's explore the key topics that await you.

Our course will explore three fundamental areas of Computational Intelligence:

1. Neural Networks:

   • Inspired by biological nervous systems, neural networks play a crucial role in transforming input to output.
   • Types of neural networks include feed-forward networks, self-organizing maps, recurrent networks, ART and Hopfield neural networks.
   • Our research challenge: How do we effectively train neural networks?

2. Evolutionary Algorithms (EAs):

   • EAs aim to find plans that optimize a given fitness function.
   • Examples include solving the traveling salesman problem using genetic algorithms.
   • We'll explore nature-inspired optimization techniques, such as genetic algorithms, particle swarm optimization, bee colony, and artificial ants.

3. Fuzzy Logic and Fuzzy Set Theory:

   • Fuzzy logic allows us to represent "fuzzy" knowledge, which is less sensitive to errors or noise.
   • Applications include building control systems and calculating overall quality (fitness) in various scenarios.

• Basic Knowledge: You should have a solid understanding of artificial intelligence concepts.
• Mathematics: Advanced topics may require strong mathematical foundations.

• Pythorch Workshop
• Meta Heuristic Algorithms(Draft)
• Some Published Papers
• Haykin, S. S. (2009). Neural Networks and Learning Machines (3rd ed.). Prentice Hall.PDF
• طاهری، س.م. (1375)، آشنایی با نظریه مجموعه­ های فازی (تالیف)، انتشارات جهاد دانشگاهی دانشگاه فردوسی مشهد (چاپ دوم: 1378)
• Zimmermann, H.-J. (2001). Fuzzy Set Theory-and Its Applications, Fourth Edition. Prentice Hall. PDF

• Homework – 40%
  
• Midterm – 20%
  — Will consist of mathematical problems and/or programming assignments.
• Seminars - 10%
• Final – 30%

Honesty and integrity are vital elements of the academic works. All your submitted assignments must be entirely your own (or your own group's).

We will follow the standard of Faculty of Mathematical Sciences approach:

• You should not use code of others or be looking at code of others when you write your own: You can talk to people but have to write your own solution/code
• You can talk to others about the algorithm(s) to be used to solve a homework problem; as long as you then mention their name(s) on the work you submit

I will be having office hours for this course on Monday (10:00 AM--11:30 AM). If this is not convenient, email me at [email protected], talk to me after class or schedule an appointment via Calendly.

Come and join our Slack group to engage in course discussions.