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The course aims at providing students with a solid understanding of intelligent agents and multi-agent systems (MAS), focusing on both theoretical foundations and practical applications. It explores key concepts such as autonomy, agent-based architectures, automatic reasoning, and Bayesian networks. Students will examine emerging paradigms, including agentic AI and neuro-symbolic agents, and will gain hands-on experience with technologies and platforms for building and deploying intelligent agents, including logic programming. Finally, agent-based principles, technologies, and methods will be exploited as the foundations for the engineering of intelligent systems.
course contents
Foundations of Artificial Intelligence
Intelligence and Truth
Symbolic vs Subsymbolic vs Nonsymbolic Techniques
Symbolic AI
Logic & Logic Programming / Prolog
Constraint Programming / MiniZinc
Automatic Reasoning
Planning / STRIPS
Foundations of Agency
Intelligence vs. Autonomy
BDI Logic & Architectures / Jason
Reasoning with uncertainty: Probabilistic Reasoning, Fuzzy Logic, Bayesian Reasoning
