Center for Analysis and Design of Intelligent Agents

T-713-MERS-2026 Links to Thórisson's Lecture Notes

Background Concepts
- Artificial Neural Networks (ANNs)
W1: INTRODUCTION
- Concepts & Terms
- Empirical Reasoning - Preface
W2: DATA, WORLDS & EMPIRICISM
- Key concepts: Environment, tasks, entities, variables, experiments, data
- Worlds, Empiricism
W3: Task Theory
- Key concepts: Tasks, agent perspective, observer perspective, intricacy
- Task Theory
Sprint W4+W5: LEARNING, KNOWLEDGE & MODELING
- Key concepts: Learning, knowledge, information, representation, cause-effect
- Learning & Knowledge
Sprint W6+W7: REASONING I: THE BASICS
- Key concepts: Syllogism, logic, reasoning
- Intro to Reasoning
Sprint W8+W9: REASONING II
- Key concepts: argument, defeasibility, background assumptions, context
- Empirical Reasoning I
- Empirical Reasoning II
Sprint W10+11: REASONING ARCHITECTURES & MORE
- Key topics: Causation, methodology, architectures and NARS assignments (see Canvas)
- Empirical Reasoning III
- Empirical Reasoning IV
W12: WRAP-UP
- Methodological Considerations