Part 1: Knowledge Representation, Reasoning, and Semantic Technologies


Introduction to Knowledge-Based Systems and to Knowledge Representation
Rational agents and their environments: from reactive agents to autonomous agents. The general SOAR cognitive architecture.
Reasoning: deductive and inductive reasoning; reasoning with uncertainty; case-based reasoning. Bayes networks and probabilistic inference
Problem solving: search strategies and optimization
The Logic approach: First order logic and logic programming. Fuzzy logic and the computing with words approach. Strengths and limitations.
The Semantic Web: The RDF Data Model. OWL: The Web Ontology Language. Ontology Engineering. Examples in Protege. The SPARQL query language. Reasoners. Other Semantic Web Technologies and Applications. Linked data.


Part 2: Machine learning and knowledge discovery from large scale multimedia data


Supervised learning: Regression, Support Vector Machines, Decision trees, KNN
Neural models: networks, model design, backpropagation, Gradient descent. Model capacity, overfitting and underfitting, regularization.
Deep Learning: tensors, deep learning frameworks, data augmentation, training strategies.
Deep learning Architectures: Convolutional Neural Networks (CNN) ; Recurrent Neural Networks (RNN); Autoencoders; GAN and CGAN
Problem solving through natural computation: reinforcement learning and evolutionary algorithms.
Multimedia analysis: Fundamental of multimedia signal processing (audio, video, biosignals). Image representations. Artificial vision. Object detection and recognition. Semantic segmentation. Text representations.
Knowledge discovery from data: the general data mining process, model construction and testing, performance evaluation and metrics, validation, cross-validation, visualization, model explainability.
Applications



Part 3: Autonomous agents and the NAO humanoid robotic platform


Theories of perception, action and interaction. Interactive autonomous agents. Human-robot interaction
The Nao robot operating system (NAOqi), the graphical programming environment Choreographe, NAO SDK.
Applications. Augmenting the NAO perceptual and cognitive system.

Selected chapters from the following resources:


Artificial Cognitive Systems: A Primer. David Vernon, MIT Press, 2014
Artificial intelligence: a modern approach. Stuart Russell, Peter Norvig, 3rd edition, 2010
Data Mining: The Textbook, Charu Aggarwal, 2015. Springer
Deep Learning. I. Goodfellow, Y. Bengio and A. Courville, MIT Press, 2016
A semantic Web Primer (third edition). Grigoris Antoniou, Paul Groth, Frank van Harmelen, and Rinke Hoekstra, 2012. The MIT Press, Cambrigde, Massachusetts, London, England.
Teaching materials provided by the instructor