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IPLUSO 2129

Artificial Intelligence

Computer Engineering and Applications
  • ApresentaçãoPresentation
    The scope of the artificial intelligence course aims to provide students with a comprehensive understanding of the fundamental concepts, techniques and applications of AI environments, preparing them for emerging areas with future positions related to these concepts.
  • ProgramaProgramme
    Introduction to AI: Definition, history, approaches and systems of AI; Characteristics of environments and performance indicators; Branches and scientific areas of AI. Declarative Programming (Logic/Functional): Introduction to reasoning and knowledge representation; Propositional and First Order Logic; Informed, uninformed, local and adversarial search. Intelligent Agents: Concepts of rationality and environments; Types and classes of agents, functions, applications and performance measures. Scheduling Problems: Definitions, classification and approaches; Constraint satisfaction problems and adversarial search. Learning Algorithms: Genetic, reinforcement, supervised and unsupervised algorithms; Minimum-maximum algorithm, alpha-beta pruning, imperfect information games and multi-player games. Meta-heuristics and Hipe-heuristics: Case studies. Fuzzy Logic and Mixed Systems (Neuro-Fuzzy): Case studies.
  • ObjectivosObjectives
    Understanding the key components in the fields of artificial intelligence; Analyze artificial intelligence techniques for practical problem solving; Implementing classical artificial intelligence techniques in controlled settings; Build heuristics dedicated to the problem in question in order to improve the search; Serve as a basis for bridging various areas related to computer science.
  • BibliografiaBibliography
    [Stuart Russell], [Stuart Russell] - [ArtificialIntelligence.AModernApproach [3rdEdition,PrenticeHall,Inc.,2010; ISBN-10: 0136042597]; [Hart, P.E., Stork, D.G. and Duda, John], [Hart] - [Pattern classification ] [Willey & Sons ,ISBN-10:0471056693]; [Luger, G.F. and Stubblefield, W.A.,] [AI algorithms, data structures, and idioms in Prolog, Lisp, and Java][ 2009. Pearson Addison-Wesley, ISBN-10:0136070477]; [Burke, E. K., & Kendall, G. ] (Eds.). (2014). Search Methodologies. Springer US. https://doi.org/10.1007/978-1-4614-6940- Inteligencia Artificial, Ernesto Costa e Anabela Simões 2008 FCA Editora; Prolog Programming for Artificial Intelligence, Ivan Bratko 2001 PEARSON EDUCATION
  • MetodologiaMethodology
    Project-based learning: Projects, supported by software for validation, either through code or the use of toolboxes; Quizzes; Puzzles; Pair teaching to introduce the opportunity for independent research; Presentations of work; Allocation of class time so that students can make presentations to the class and focus on their topic. With peer learning, students are able to develop skills of various kinds, such as self-study and the ability to make technical-scientific communications.
  • LínguaLanguage
    Português
  • TipoType
    Semestral
  • ECTS
    6
  • NaturezaNature
    Mandatory
  • EstágioInternship
    Não