1ª aula
Presentação: Organization, Program, Introduction
What is machine learning: examples, symbolic and statistical learning
1ª aula
Presentação: Organization, Program, Introduction
What is machine learning: examples, symbolic and statistical learning
2ª aula
Perceptron, Backpropagation, RBF network, Kernel trick
3ª aula
The Brain and Information
4ª aula
Knowledge and Learning: EBL, Domain Theory, Analogical Reasoning, Verbal Categories, Visual Categories, Reinforcement Learning
5ª aula
Reinforcement Learning: Passive learning vs. Active Learning, LMS, ADP, TD, Q-Values, Explicit Representation, Genetic Algorithms and Reinforcement Learning
6ª aula
Analogy,Multidimensional Scaling,Structure Mapping Engine,Copycat,PR and AI, Bongard problem, Letter Spirit, Invariant Pattern recognition, Hierarchical Networks, Information and Contours
7ª aula
Cognitive Systems, Soar, Chunking-based Learning, Associative Computing, Learning
8ª aula
The “ideal ra(onal agent” in Ulmatum Game
9ª aula
Quantum Probabilisc Graphical Models for Decision and Cognion
by
Catarina Pinto Moreira
10ª aula
ETL
by
João Pereira
11ª aula
Autonomic Computing: notions, implementations and challenges
by
Richard Gil Martinez