Autonomous and Adaptive Systems 2019-2020
Overview
The goal of this module is to provide a solid introduction to the design of autonomous and adaptive computing systems from a theoretical and practical point of view. Topics will include principles of autonomous system design, reinforcement learning, game-theoretic approaches to cooperation and coordination, bio-inspired systems, complex adaptive systems, and computational social systems. The module will also cover several practical applications from a variety of fields including but not limited to distributed and networked systems, mobile and ubiquitous systems, robotic systems, and vehicular and transportation systems.
Link to official course page containing syllabus and textbooks
Notices
The oral exams will take place on 22 June 2020, 13 July 2020 and 20 July 2020. Please check the first deck on slides containing administrivia and information about the exam (and the programming project to be submitted).
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Slides
Introduction to Intelligent and Autonomous Agents
Introduction to Reinforcement Learning
Introduction to Deep Learning I
Introduction to Deep Learning II
Value Approximation Methods in Reinforcement Learning
Deep Reinforcement Learning in TensorFlow - Advanced Topics
Autonomous Robots and Self-driving Cars
AI and Creativity: Generative Machine Learning
Python Notebooks
Notebook TF-agents DQN Atari Games
Last updated: 7 June 2020