https://github.com/srosalino/intelligent_systems_investigations

Series of 11 works, covering: State-Space Representations, Search, Adversarial Search, Logic, Automated Reasoning, Reasoning with Uncertainty and Vagueness and Machine Learning
https://github.com/srosalino/intelligent_systems_investigations

adversarial-search artificial-intelligence automated-reasoning machine-learning reasoning-under-uncertainty state-space-representation

Last synced: about 1 month ago
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Series of 11 works, covering: State-Space Representations, Search, Adversarial Search, Logic, Automated Reasoning, Reasoning with Uncertainty and Vagueness and Machine Learning

• Host: GitHub
• URL: https://github.com/srosalino/intelligent_systems_investigations
• Owner: srosalino
• Created: 2024-07-11T22:39:37.000Z (5 months ago)
• Default Branch: master
• Last Pushed: 2024-07-11T22:50:23.000Z (5 months ago)
• Last Synced: 2024-07-12T01:08:06.927Z (5 months ago)
• Topics: adversarial-search, artificial-intelligence, automated-reasoning, machine-learning, reasoning-under-uncertainty, state-space-representation
• Language: Jupyter Notebook
• Homepage:
• Size: 4.31 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Vrije Universiteit Amsterdam Intelligent Systems Program

**Course Objective**

Knowledge and understanding: at the end of the course, the students will be familiar with basic knowledge of some of the core aspects of AI: state-space representations, search, adversarial search, logic, automated reasoning, reasoning with uncertainty and vagueness and machine learning. Applying knowledge and understanding: students will be able to implement basic (adversarial) search algorithms, as well as knowledge based and adaptive methods to build Intelligent Agents. Making judgements: the students will have a basic understanding of the ethical and societal implications of the developements in AI. Communication skills: students will be able to write a scientific reports about an original research question in a group of students. Learning skills: students will be trained in acquiring a set of complex AI related topics in a restricted period of time, come up with an original research question and perform the necessary (empirical) research.

**Course Content**

The course will provide an introduction to some of the basic concepts of Artificial Intelligence, such as search, adversarial search, knowledge representation and machine learning.