"Hinweis: Die Informationen auf dieser Seite dienen zur Ergänzung des Vorlesungsverzeichnisses (VVZ). In Zweifelsfällen gelten immer die offiziellen Angaben im VVZ."
Over the past years, the appearance of applications requiring or benefiting from (classical) artifical intelligence has accelerated. For example, electronic markets for the buying and selling of goods and services over the Web is a fast-growing, multi-billion-dollar segment of the world economy. Knowledge-based techniques for product recommendation, auctions, need identification, vendor selection, negotiation, agent communication, ontologies, business rules, and information integration are of rising interest and have started having practical impact on real Web e-markets.
This class covers the foundational theories (mostly) from the field of (classical) artificial intelligence that have made it possible to evolve to more “intelligent” applications. It will cover areas such as knowledge representation and reasoning (increasingly important through the semantic web effort of the w3c), problem solving, planning, and reasoning under uncertainty. For each of the subjects it will cover the underlying theories and provide a insight into practical applications using those techniques
Please note that though this class does not attempt to answer the grand old question of artificial intelligence: how to build an artificial intelligence. Its goal is to present methods found during this quest that have been surprisingly useful in practical applications.
The lectured take place on Tuesday, 2 - 3:45 pm in BIN-2.A.01.
The exam will take place on Tuesday, June 7th, 2011, 2 pm.
Please note that the official page on the VVZ is relevant with respect to all information retaining exams.
A full syllabus draft will be available as PDF.
We will use: S. Russel's & P. Norvig's Artificial Intelligence: A Modern Approach (Third Edition, Pearson).
- The Readings below are listed as the chapters in the third edition!
- Chapters 3 and 4 are available in PDF here.
- You can find a downloadable version of the book here (they offer student discounts).
Some additional papers and books. To be announced!
- Assignment 1, Due Date 22nd of Marchh
- Assignment 2, Due Date 12th of April
- Assignment 3, Due Date 17th of May
There will be 3 assignments. Each assignment accounts for 10% of the final grade (all together 30% of your final grade). We expect all students to collect at least half of all the assignment points.
|Part 1: Intelligent Search - Problem Solving and Planning as Search, Search|
|Di||1.3.||Informed Search||3, 4||A1 out|
|Di||8.3.||Constraint Satisfaction, Adversarial Search||5, 6|
|Part 2: Knowledge intensive processing|
|Di||15.3.||Logic review (Propositional Logic, First Order Logic)||7,8|
|Di||22.3.||Logical Programming||A1 back, A2 out|
|Di||29.3.||Logical Programming, Knowledge Representation||12|
|Part 3: Uncertainty, probability, learning and probabilistic reasoning|
|Di||5.4.||Modeling uncertainty - probability revisited||13|
|Di||12.4.||Induction Part I: Decision Trees||18.1-18.4||A2 back, A3 out|
|Di||19.4.||Bayesian Belief Networks||14|
|Di||3.5.||Bayesian Belief Networks, Probabilistic Reasoning||14|
|Di||10.5.||Reasoning over time - (hidden) Markov models||15|
|Di||17.5.||Induction Part II: Naive Bayes||A3 back|