Lectures-Resources

For up-to-date information check out the Artificial Intelligence VIMIAC10 Teams group 2023 Fall:

https://teams.microsoft.com/l/team/19%3aJ82avPGXiagGTNcjdXkcH-AjA43H1lJhLC99oZyDLmk1%40thread.tacv2/conversations?groupId=fb68f270-eab6-4e0b-b6a1-caa49b7ea465&tenantId=6a3548ab-7570-4271-91a8-58da00697029


Lectures from previous semesters

Lecture 1:

Introduction slides

Additional material:
Stuart Russell, Provably Beneficial AI,
http://home.mit.bme.hu/~tade/reports-on-ai-future/russell-ijcai17-pbai.pptx

Lecture 2:

Uninformed search algorithms
Example

Additional materials:

A_pigeon_solves_the_classic_box-and-banana_problem
https://www.youtube.com/watch?v=mDntbGRPeEU

Are_crows_the_ultimate_problem_solvers
https://www.youtube.com/watch?v=AVaITA7eBZE

Lecture 3:

Informed search

Additional materials:

A zip file containing:
Greedy Search example, A* example (A* contours), Hill climbing search example,
Recursive Best-first Search example, Unifrom cost search example, Simulated annealing

Lecture 4:

Adversarial search

Additional materials:

Genetic algorithms

Lecture 5:

Constraint satisfaction problems (CSP)

Additional materials:

Arc consistency checking

Lecture 6:

Propositional logic, inference

(See the bottom of the page for slides L4-L6)

Lecture 7:

First-order logic

(See the bottom of the page for slide L8)

Lecture 8:

Uncertainty, Bayesian networks, probabilistic inference

(See the bottom of the page for slides L10, L11, L12)

Lecture 9:

Decision theory, decision networks, recommendation systems

(See the bottom of the page for slides L12, L13)

Lecture 10:

Midterm preparation

 

Lecture 11:

Recommendation systems

AI_collab-filtering-tutorial_2019.ppt

AI_eng_matrix_factorization_2019.pptx

Lecture 12:

Supervised learning, decision trees
AI_2017_Learning_v1.pptx

Lecture 13:

Neural networks
VIMIAC10-2019-Introduction_to_Neural_Networks.pptx

Lectures 14-15:

Cooperative agents
AI_Cooperative-Agent-Systems-L5-2019.pdf

Lecture 16:

Distributed learning
AI_Learning-in-Agent-Systems-L6-2019.pdf

Lecture 17:

Semantic technologies, description logic

Lecture 18:

Artificial general intelligence

Lecture 19:

Endterm preparation - 9th December 2019, Monday 14:15-16:00, Room IE.224.
VIMIAC10-2019-12-ZH2-Tests_Tasks_EN.pptx

 

Book:

S. Russell and P. Norvig Artificial Intelligence: A Modern Approach Prentice Hall, 2003, Second edition or higher.

Suggested reading:

 

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