First Semester
Fri: 11:00 a.m. - 1:00 p.m., Room E4
Fri: 2:00 p.m. - 4:00 p.m., Room E4
Introduction [pdf]
Alan Turing (Wikipedia)
Computer chess (Wikipedia)
Shannon, C., "Programming a Computer for Playing Chess", Philosophical Magazine, 41 (314), 1950 [pdf]
Campbell, M., Hoane, A. J., Hsu, F., "Deep Blue", Artificial Intelligence, 134 (1-2), 2001 [pdf]
"Building Watson - A Brief Overview of the DeepQA Project", YouTube, 2011 [video]
"Final Jeopardy! and the Future of Watson", TED, 2011 [video]
Ferrucci, D., et al., "Building Watson: An Overview of the DeepQA Project", AI Magazine, 3 (31), 2010 [pdf]
Mnih, V., Kavukcuoglu, K., Silver, D., Graves, A., Antonoglou, I., Wierstra, D., Riedmiller, M., "Playing Atari with Deep Reinforcement Learning", arXiv, 2013 [arXiv]
Symbolic reasoning [pdf]
Language, schemas and reasoning
Syllogism (ancient logic) (Wikipedia)
Propositional logic [pdf]
Boolean algebras, formal propositional language and its semantics, satisfiability, entailment
Rules of inference, justified by entailment (Wikipedia)
Entailment and algorithms [pdf]
Decision problems, entailment as a satisfiability problem (i.e. refutation), semantic tableaux
Tree Proof Generator [link]: online solver through semantic tableaux
Propositional resolution [pdf]
Resolution as inference rule, propositional resolution by refutation
First-Order logic [pdf]
First-Order semantic structures, language, validity
Semi-decidability of First-Order logic [pdf]
Prenex normal form, skolemization, Herbrand's theorem
Prenex normal form (Wikipedia)
First-Order resolution [pdf]
Clausal form, unification, resolution method for first-order logic
SLD resolution [pdf]
Horn clauses, SLD resolution, logic programming
All Prolog examples are compatible with SWI-Prolog (free software) [link]
Minimal models, logic programs [pdf]
Herbrand models, minimal models, logic programming systems
Plausible reasoning [pdf]
Negation as failure, closed world assumption, deductive, inductive and abductive reasoning
Probabilitistic reasoning: representation and inference [pdf]
Foundations of probability, probability space, random variables, Bayes' theorem, probabilistic inference
Countable set (Wikipedia)
Sigma algebra
(Wikipedia - see simple set-based examples)
Probability space (Wikipedia)
Random variable (Wikipedia)
"The Banach-Tarski Paradox" (semi-serious but also very informative), YouTube, 2015 [video]
Graphical models [pdf]
Graphical models and factorization, d-separation, inference, computational methods
Examples with "Bayes" (free software) available on AISpace
[download] (see Belief and Decision Networks)
Supervised learning [pdf]
Learning proababilities from observations: maximum likelihood estimator, maximum a posteriori probability,
conjugate prior distribution
Conjugate prior (Wikipedia)
Unsupervised learning [pdf]
Learning from incomplete observations: k-means, hidden random variables, EM algorithm. An example: latent Dirichlet allocation (LDA)
A simple Java implementation of the EM algorithm for coin tossing [zip]
Reinforcement learning [pdf]
Multi-armed bandits and methods, Thompson sampling, Markov Decision Processes, value function, optimal policy, iterative learning algorithms
Sutton, R.S., Barto, A.G., Reinforcement Learning: An Introduction, 2nd Edition (draft)
[link]
(at this time, the draft is freely available at the above link)
Reinforcement Learning Simulator: a demo for the maze example implemented in Java [link]
Online learning and self-organizing systems [pdf]
Simple and exponential moving averages: a worksheet example [xlsx]
Fritzke, B., Some Competitive Learning Methods, Ruhr-Universität Bochum, TR, 1997
[pdf]
Self-Organizing Networks
[Java applet]
SOAM: self-organizing adaptive maps, seminar presentation [pdf]
Marco Piastra
Contact: marco.piastra@unipv.it
Mordechai Ben-Ari. Mathematical Logic for Computer Science (3rd Edition). Springer, 2012
Artificial Intelligence: A Modern Approach (3rd Edition). Prentice Hall, 2009.