| Title | Decision theory | |
| Duration | 60 | |
| Module | A | |
| Lesson Type | Lecture | |
| Focus | Technical - Foundations of AI | |
| Topic | Foundations of AI |
consequentialism, subjectivism, probability theory, utility theory, decision theory, optimal decision, bounded rationality, satisficing, cognitive bias, effective altruism, off-switch game, sequential decisions, value of information, multi-armed bandit, exploration-exploitation dilemma,
The materials of this learning event are available under CC BY-NC-SA 4.0.
| Duration | Description | Concepts | Activity | Material |
|---|---|---|---|---|
| 5 | Sources of uncertainty and Interpretations of probability | uncertainty | ||
| 5 | Bernoulli and multinomial distributions | univariate distributions | ||
| 5 | Axioms of probability theory (additivity) | probability theory | ||
| 5 | Elements and graphical notation of a single-step decision problem: the decision network of stochastic→utility/loss←action nodes | decision problem | ||
| 5 | Utility and loss functions, common loss functions and matrices | preferences | ||
| 5 | Expected value, the maximum expected utility principle | optimal decision | ||
| 5 | Conditional probability and Bayes' theorem (for two variables and with condition) | conditional probability | ||
| 5 | Independence and conditional independence | independence | ||
| 5 | Example of a Naive Bayesian network | Naive Bayes net | ||
| 5 | Example of decision network based on a Naive Bayesian network | |||
| 5 | Posterior inference and selection of optimal decision | posterior inference | ||
| 5 | Between evidence inference and calculation of the value of information | value of information |
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The Human-Centered AI Masters programme was co-financed by the Connecting Europe Facility of the European Union Under Grant №CEF-TC-2020-1 Digital Skills 2020-EU-IA-0068. The materials of this learning event are available under CC BY-NC-SA 4.0
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The HCAIM consortium consists of three excellence centres, three SMEs and four Universities
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