
Departamento de Ciência de Computadores
Disciplina: Sistemas Inteligentes / Inteligência Artificial
Important Note
Academic Misconduct
All examinations, programming assignments, and written homeworks must
be done by each team. Cheating and plagiarism will be dealt with in
accordance with University procedures (see below the two documents
related to the topic). Hence, code and reports for programming
assignments should not be shared across teams. You are encouraged to
discuss ideas, approaches and techniques with your peers, but code and
reports should be unique for each team. Additionally, text written in
reports should not be copied from internet sources. The same
holds true for code.
Please, have a look at the documents below.
Important Dates
Theoretical Classes
Class 1 (Feb 06): Introduction
Class 2 (Feb 09): Procura não informada (revisão de busca em largura e profundidade)
Class 3 (Feb 13): Procura não informada (procura limitada em profundidade, iterativa em profundidade, de custo uniforme, bidirecional)
Class 4 (Feb 16): Procura informada (guloso com heurística, A*, IDA*, RBFS)
Class 5 (Feb 20): Procura informada (Exemplo de execução do algoritmo A*) (cont.) e verificação de solvabilidade de problemas N*N-1
Class 6 (Feb 23): Procura informada (guloso com heurística, IDA*, RBFS) (cont.)
Class 7 (Feb 27): Algoritmos de melhoramento iterativo
Mar 02: Dias Abertos (Open Day UP): no class
Class 8 (Mar 06): Algoritmos
de melhoramento iterativo: Simulated Annealing e Algoritmos Genéticos
Class 9 (Mar 09): Adversarial Search: minimax and alpha-beta pruning
Class 10 (Mar 13): Adversarial Search: minimax and alpha-beta pruning (cont.)
- Presentation by Tadeu Freitas and Nuno Silva: xadrez robótico (video1, video2)
- Presentation by Jhonny Moreira: Monte Carlo Tree Search (slides)
Class 11 (Mar 16): Adversarial Search: minimax and alpha-beta pruning (cont.)
Class 12 (Mar 20): FIRST TEST
Class 13 (Mar 23): Constraint Satisfaction Problems
Class 14 (Mar 27): Introduction to Prolog (language basics and theory)
Class 15 (Mar 30): Introduction to Prolog (DCGs and other example)
Class 16 (Apr 3): Introduction to Planning
Class 17 (Apr 6): Planning: POP and CPOP
Apr 10, 13, 17: Happy Easter!
Class 18 (Apr 20): Planning: CPOP (threat resolution)
Class 19 (Apr 24): Machine Learning: Decision Trees
Class 20 (Apr 27): Machine Learning: Decision Trees (cont.)
May 1st: Labour Day
Class 21 (May 4): Probabilistic Models
May 8-12: Academic Week
Class 22 (May 15): Probabilistic Models (cont.)
Class 23 (May 18): Neural Networks
Class 24 (May 22): Neural Networks (cont.) and Review
Class 25 (May 24): SECOND TEST
Practical Classes
Week 1 (Feb 06-10): resolução de problemas e
estratégias mentais
(jogo dos oito, n-rainhas, jogo do galo e extração de padrões)
Week 2 (Feb 13-17): Trabalho 1: Procura inteligente (pdf, html)
Week 3 (Feb 20-24): Trabalho 1: Procura inteligente (cont.) (pdf, html)
Week 4 (Feb 27-Mar 03): Trabalho 1: Procura inteligente (cont.) (pdf, html)
Week 5 (Mar 06-10): Trabalho 2: Adversarial Search (pdf, html)
Week 6 (Mar 13-17): Trabalho 2: Adversarial Search (cont.) (pdf, html)
Week 7 (Mar 20-24): Trabalho 2: Adversarial Search (cont.) (pdf, html)
Week 8 (Mar 27-31): Trabalho 3: Using Prolog (pdf, html)
Week 9 (Apr 3-7): Trabalho 3: Using Prolog (cont.) (pdf)
Apr 10-14: EASTER WEEK
Week 10 (Apr 17-21): Trabalho 3: Using Prolog (cont.) (pdf)
Week 11 (Apr 24-28): Trabalho 4: Decision Trees (pdf, html)
Week 12 (May 1-5): Trabalho 4: Decision Trees (cont.) (pdf, html)
May 8-12): ACADEMIC WEEK
Week 13 (May 15-19): Trabalho 4: Decision Trees (cont.) (pdf, html)
Recommended Reading
What is the Turing Test? (seminal article by Alan Turing)
3,000,000
queens in less than one minute (Artigo sobre soluções
eficientes para o problema das n-rainhas - pdf )
Links of interest
MIT News - AI
Science Daily - IA
AI News
The Future of AI (essay)
Artificial Intelligence: a Modern Approach
Weka
RapidMiner
Yap Prolog
Aleph