Intelligent Systems Engineering 2023/2024

At the end of the course, students get acquainted with the fundamental issues of intelligent systems, the most relevant computational models and technologies, and the most effective methods. In particular, students become familiar with the fittest solutions, languages, technologies, architectures, and methodologies to design intelligent systems, and are capable of

• devising the problems requiring artificial intelligence techniques for their solution;
• determining the most proper conceptual and methodological approaches;
• selecting and integrating the fittest technologies for implementing the solutions detected.

• Case Studies
  ChatGPT—Beyond the Turing Test  •  Autonomy in Biology  •  Programming Intentional Agents in AgentSpeak(L) & Jason  •  Natural Language Processing
• General Issues of Intelligent Systems
  Drivers for Intelligent Systems  •  On Autonomy: Concepts & Definitions  •  Agents for Intelligent Systems Engineering  •  Artificial Intelligence: A Short Story  •  Automated Reasoning  •  Reasoning Agents  •  Logic & Computation  •  Planning for Intelligent Agents  •  Self-Organising Systems  •  Nature-Inspired Coordination & Self-Organisation  •  Interacting with Autonomous Systems: Conversational Informatics  •  Simulation & Multi-Agent Systems
• Technologies for Intelligent Systems
  Knowledge Representation  •  Inference  •  Perception and Actuation  •  Planning with STRIPS  •  Programming Intentional Agents: Exercises in Jason  •  Introduction to eXplainable Artificial Intelligence (XAI)
• Scientific Competences
  Sources of Scientific Literature for Intelligent & Autonomous Systems  •  Systematic Literature Review as a Methodology for Scientific Surveys

• Lessons with slides shared with students
• Examples and case studies discussed  by the teachers
• Lab activity

• Verification of lab activity
• Presentation and discussion of an individual/group project