Artificial and Evolutionary IntelligenceModule Artificial and Swarn Intelligence
Academic Year 2025/2026 - Teacher: MARIO FRANCESCO PAVONEExpected Learning Outcomes
The course aims to explore the new AI frontiers on distributed and self-organizing methodologies, focusing on intelligent agents inspired by natural collective behavior. Specifically, it aims to provide a theoretical and practical understanding of how to design, model, and analyze intelligent systems, composed of multiple autonomous entities that learn and interact wiht each other and the environment to achieve common goals.
The goal of the course is to provide to each student:
1) good knowledge on the basic concepts;
2) good knowledge on design and modeling agent-based models, and collective behaviors;
3) excellent ability to design robust, flexible and scalable algorithms.
Course Structure
Classroom-taught lessons. Can be also included external seminars held by expert researchers on related topics.
Should teaching be carried out in mixed mode or remotely, it may be necessary to introduce changes with respect to previous statements, in line with the programme planned and outlined in the syllabus.
Learning assessment may also be carried out on line, should the conditions require it.
Required Prerequisites
Attendance of Lessons
Detailed Course Content
2. Agent-based models as Recursive Systems
3. Agents’ behavior and learning
4. Agent-based models in complex systems
5. Swarm Intelligence and Collective Behaviors
6. Foundations of Swarm Intelligence
7. Swarm and Collective Intelligence
8. Algorithms of Swarm Intelligence
9. Applications of Swarm Intelligence
Textbook Information
- M. Sotomayor, D.Perez-Castrillo and F. Castiglione, “Complex Social and Behavioral Systems: game theory and agent-based models”, Springer, 2020 (part II)
- U. Wilensky and W. Rand, “An introduction to Agent-Based Modeling: modeling, natural, social and engineered complex systems with NetLogo”, MIT Press, 2015
- D. Delli Gatti, G. Fagiolo, M. Gallegati, M. Richiardi and A. Russo, “Agent-Based Models in Economics”, Cambridge University Press, 2018
- G. Weiss, “Multiagent Systems”, MIT Press, 2013
- H. Iba, “Agent-Based Modeling and Simulation with Swarm”, CRC Press, 2013
- Eric Bonabeau, Marco Dorigo, and Guy Theraulaz, “Swarm Intelligence: From Natural to Artificial Systems”, Santa Fe Institute Studies on the Sciences of Complexity, 1999.
- K.S. Kaswan, J.S. Dhatterwal and A. Kumar, "Swarm Intelligence: An Approach from Natural to Artificial”, Wiley, 2023
Course Planning
| Subjects | Text References | |
|---|---|---|
| 1 | Agent-based models | 1) M. Sotomayor, D.Perez-Castrillo and F. Castiglione, “Complex Social and Behavioral Systems: game theory and agent-based models”, Springer, 2020 (part II); 2) U. Wilensky and W. Rand, “An introduction to Agent-Based Modeling: modeling, natural, social and engineered complex systems with NetLogo”, MIT Press, 2015; 3) D. Delli Gatti, G. Fagiolo, M. Gallegati, M. Richiardi and A. Russo, “Agent-Based Models in Economics”, Cambridge University Press, 2018; 4) G. Weiss, “Multiagent Systems”, MIT Press, 2013 |
| 2 | Agent-based models as Recursive Systems | D. Delli Gatti, G. Fagiolo, M. Gallegati, M. Richiardi and A. Russo, “Agent-Based Models in Economics”, Cambridge University Press, 2018 |
| 3 | Agents’ behavior and learning | 1) M. Sotomayor, D.Perez-Castrillo and F. Castiglione, “Complex Social and Behavioral Systems: game theory and agent-based models”, Springer, 2020 (part II); 2) U. Wilensky and W. Rand, “An introduction to Agent-Based Modeling: modeling, natural, social and engineered complex systems with NetLogo”, MIT Press, 2015; 3) D. Delli Gatti, G. Fagiolo, M. Gallegati, M. Richiardi and A. Russo, “Agent-Based Models in Economics”, Cambridge University Press, 2018; 4) G. Weiss, “Multiagent Systems”, MIT Press, 2013 |
| 4 | Agent-based models in complex systems | 1) M. Sotomayor, D.Perez-Castrillo and F. Castiglione, “Complex Social and Behavioral Systems: game theory and agent-based models”, Springer, 2020 (part II); 2) U. Wilensky and W. Rand, “An introduction to Agent-Based Modeling: modeling, natural, social and engineered complex systems with NetLogo”, MIT Press, 2015; 3) D. Delli Gatti, G. Fagiolo, M. Gallegati, M. Richiardi and A. Russo, “Agent-Based Models in Economics”, Cambridge University Press, 2018; 4) G. Weiss, “Multiagent Systems”, MIT Press, 2013 |
| 5 | Swarm Intelligence and Collective Behaviors | 1) H. Iba, “Agent-Based Modeling and Simulation with Swarm”, CRC Press, 2013; 2) Eric Bonabeau, Marco Dorigo, and Guy Theraulaz, “Swarm Intelligence: From Natural to Artificial Systems”, Santa Fe Institute Studies on the Sciences of Complexity, 1999; 3) K.S. Kaswan, J.S. Dhatterwal and A. Kumar, "Swarm Intelligence: An Approach from Natural to Artificial”, Wiley, 2023 |
| 6 | Foundations of Swarm Intelligence | 1) H. Iba, “Agent-Based Modeling and Simulation with Swarm”, CRC Press, 2013; 2) Eric Bonabeau, Marco Dorigo, and Guy Theraulaz, “Swarm Intelligence: From Natural to Artificial Systems”, Santa Fe Institute Studies on the Sciences of Complexity, 1999; 3) K.S. Kaswan, J.S. Dhatterwal and A. Kumar, "Swarm Intelligence: An Approach from Natural to Artificial”, Wiley, 2023 |
| 7 | Swarm and Collective Intelligence | 1) H. Iba, “Agent-Based Modeling and Simulation with Swarm”, CRC Press, 2013; 2) Eric Bonabeau, Marco Dorigo, and Guy Theraulaz, “Swarm Intelligence: From Natural to Artificial Systems”, Santa Fe Institute Studies on the Sciences of Complexity, 1999; 3) K.S. Kaswan, J.S. Dhatterwal and A. Kumar, "Swarm Intelligence: An Approach from Natural to Artificial”, Wiley, 2023 |
| 8 | Algorithms of Swarm Intelligence | 1) H. Iba, “Agent-Based Modeling and Simulation with Swarm”, CRC Press, 2013; 2) Eric Bonabeau, Marco Dorigo, and Guy Theraulaz, “Swarm Intelligence: From Natural to Artificial Systems”, Santa Fe Institute Studies on the Sciences of Complexity, 1999; 3) K.S. Kaswan, J.S. Dhatterwal and A. Kumar, "Swarm Intelligence: An Approach from Natural to Artificial”, Wiley, 2023 |
| 9 | Applications of Swarm Intelligence | 1) H. Iba, “Agent-Based Modeling and Simulation with Swarm”, CRC Press, 2013; 2) Eric Bonabeau, Marco Dorigo, and Guy Theraulaz, “Swarm Intelligence: From Natural to Artificial Systems”, Santa Fe Institute Studies on the Sciences of Complexity, 1999; 3) K.S. Kaswan, J.S. Dhatterwal and A. Kumar, "Swarm Intelligence: An Approach from Natural to Artificial”, Wiley, 2023 |
Learning Assessment
Learning Assessment Procedures
The evaluation is based as follows:
THEORY TEST: written test relating to the topics covered by the course.
PROJECT: developing an agent-based model and/or a swarm intelligence algorithm able to investigate and/or solve a given complex problem.
ORAL INTERVIEW: oral discussion on course theoretical topics and the project developed.
Students with disabilities and/or DSA must contact the teacher, the CInAP representative of the DMI and CInAP well in advance of the exam date to communicate that they intend to take the exam using the appropriate compensatory measures.