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Vorlesung Intelligent Agents and Decision Theory

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Semester:Sommersemester 2023
Dozenten:Prof. Dr. Andreas Geyer-Schulz; B.Sc. Marvin Schweizer;
Termin:Donnerstag 09:45 - 11:15
Ort:Geb. 11.40 Raum 221


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Course Description

The key assumption of this lecture is that the concept of artificial intelligence is inseparably linked to the economic concept of rationality of agents. We consider different classes of decision problems - decisions under certainty, risk and uncertainty - from an economic, managerial and AI-engineering perspective:

From an economic point of view, we analyze how to act rationally in these situations based on classic utility theory. In this regard, the course also introduces the relevant parts of decision theory for dealing with multiple conflicting objectives, incomplete, risky and uncertain information about the world, assessing utility functions, and quantifying the value of information ...

From an engineering perspective, we discuss how to develop practical solutions for these decision problems, using appropriate AI components. We introduce a general, agent-based design framework for AI systems, as well as AI methods from the fields of search (for decisions under certainty), inference (for decions under risk) and learning (for decisions under uncertainty).

Where applicable, the course highlights the theoretical ties of these methods with decision theory.

We may also discuss ethical and philosophical issues concerning the development and use of AI.


Inhalt Autor Download Literatur
Introduction Geyer-Schulz, Andreas; Schweizer, Marvin iadt_01introduction iadt_01introduction.pdf Literaturverweise (Katalog Z.L.3.IADT.1)

Intelligent Agents Geyer-Schulz, Andreas; Schweizer, Marvin iadt_02intelligent-agents iadt_02intelligent-agents.pdf, smallfsmvacuumcleaner.zip Literaturverweise (Katalog Z.L.3.IADT.2)

Trade-offs under Certainty Geyer-Schulz, Andreas; Schweizer, Marvin iadt_03_trade-offs_under_certainty iadt_03_trade-offs_under_certainty.pdf Literaturverweise (Katalog Z.L.3.IADT.3)

Search: Linear programming for decisions under certainty Geyer-Schulz, Andreas; Schweizer, Marvin iadt_04_search iadt_04_search.pdf Literaturverweise (Katalog Z.L.3.IADT.4)

Decisions under Risk Geyer-Schulz, Andreas; Schweizer, Marvin iadt_05_decisions-under-risk iadt_05_decisions-under-risk.pdf Literaturverweise (Katalog Z.L.3.IADT.5)

Information Systems Geyer-Schulz, Andreas; Schweizer, Marvin iadt_06_information-systems iadt_06_information-systems.pdf Literaturverweise (Katalog Z.L.3.IADT.6)

Bayesian Decision Networks Geyer-Schulz, Andreas; Schweizer, Marvin bayesian-decision-networks bayesian-decision-networks.pdf, studentnetwork.tgz Literaturverweise (Katalog Z.L.3.IADT.7)

Inference in Bayesian Networks Geyer-Schulz, Andreas; Schweizer, Marvin BNstudentinference.tgz , inference-in-bayesian-networks inference-in-bayesian-networks.pdf Literaturverweise (Katalog Z.L.3.IADT.8)

Learning in Bayesian Networks. Basics Geyer-Schulz, Andreas; Schweizer, Marvin learning-in-bayesian-decision-networks learning-in-bayesian-decision-networks.pdf Literaturverweise (Katalog Z.L.3.IADT.9)

Learning in Bayesian Networks. Algorithms Geyer-Schulz, Andreas; Schweizer, Marvin BNLearningAlgorithms BNLearningAlgorithms.pdf, PACBounds.R Literaturverweise (Katalog Z.L.3.IADT.10)