1ª aula
presentação: Organization, Program, Introduction
What is machine learning: examples
1ª aula
presentação: Organization, Program, Introduction
What is machine learning: examples
2ª aula
What is supervised statistical machine learning? Peceptron, Back-propagation algorithm, Kernel-machines3ª aula
4ª aula
Reinforcement Learning: Passive learning vs. Active Learning, LMS, ADP, TD, Q-Values, Explicit Representation, Genetic Algorithms and Reinforcement Learning
5ª aula
Cognitive Systems, Soar, Chunking-based Learning, Associative Computing, 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
Brain and Information
7ª aula
Cased-Based Reasoning and Games (by Samuel Mascarenhas)
8ª aula
Thermodynamics, Entropy, Macroscoping and Microscoping state, Dice model , Information and Entropy, Definition of Entropy as the number of Questions, Communication, Message, Information Theory, Representation of information, Signal alphabet, Surprise, Information and probability, Statistical encoding
9ª aula
BIOLOGICALLY INSPIRED BIOLOGICALLY INSPIRED BIOLOGICALLY INSPIRED BIOLOGICALLY INSPIRED COMPUTER MODELS COMPUTER MODELS COMPUTER MODELS FOR VISUAL RECOGNITIONFOR VISUAL RECOGNITIONFOR VISUAL RECOGNITIONFOR VISUAL RECOGNITION (by Ângelo Cardoso)
Virtual agents and learning (by Pedro Sequeira)
- Biologically Inspired Computer Models for Visual Recognition - May 2010.pdf
- PedroSequeira-ASSS-2010.pdf
- Biologically Inspired Computer Models for Visual Recognition - May 2010.pdf
- PedroSequeira-ASSS-2010.pdf
10ª aula
Brain and Memory (by João Sacramento)
Recurent Networks (by J ose Matos)
11ª aula
Cognitive Models and Interfaces (by Andreia Artífice)