Applied Computer Science and Artificial Intelligence

Artificial Intelligence and Machine Learning Unit I General goals: The course aims to introduce students to a wide-spectrum presentation of artificial intelligence (AI), with a focus on automated reasoning. Specific goals: The course pursues the objective of making students proficient in the comprehension, use, adaptation and development of solutions to a wide set of AI problems in the context of intelligent software system design, ranging from search to constraint satisfaction, from formal languages to deductive systems. Knowledge and understanding: Students will learn about core approaches and heuristics for search and constraint satisfaction problems, knowledge representation and reasoning in propositional logic and first-order logic. Applying knowledge and understanding: Learners will be able to appropriately represent AI problems from the perspective of an intelligent agent, exploit the portfolio of techniques and the different approaches shown in the course for the solution of new problems, and explain the rationale behind the autonomous decision-making process of an agent. Critical and judgmental skills: Students will be able to assess advantages and challenges in applying and adapting known techniques to design intelligent software systems, examine the environment setting, define a utility function to measure the performance of autonomous agents, and devise new solutions tailored to the novel challenges in AI. Communication skills: Learners will acquire the ability to expose their knowledge in a clear and organised manner to propose AI-based solutions, formalise the challenged problems, and effectively discuss their ideas with experts in the field. Learning capabilities: The acquired competencies will allow students to independently deepen and broaden their range of knowledge and capabilities, equipped with the necessary interpretation instruments to read published works in the scientific literature on AI autonomously.