The course "Foundations of Artificial Intelligence I" introduces into the field of artificial intelligence and one of its most important metaphors, which is metaphor of the rational agent.
The first module focuses on artificial intelligence as a research field. In the first part, this module discusses the beginnings of artificial intelligence with Alan Turing and his seminal article where he asked the question whether machines can think. We briefly touch upon the notions of symbolic and subsymbolic AI and also discuss four possible directions of AI research. We will review the Turing test as a test of intelligence and discuss a working definition for artificial intelligence. In the second part of this module, we review the history of AI and discuss 5 phases of advancement of the field of AI. The module concludes with a third part that discusses selected current challenges of AI and provides an outlook on the next decades of AI research. We touch upon current hot topic research fields such as transfer learning and reinforcement learning. With the help of examples, we will also discuss the limitations of AI systems in the understanding of unstructured information.
The second module focuses on the metaphor of the rational agent. In the first part of this module, we explore the interplay between perception, cognition, and action in an agent, and discuss how we can model intelligent agents. In the second part, we look more closely at the properties of agents and environments and discuss how agents can act successfully in different environments. In the third part, we introduce several types of agents and discuss their underlying architectures. We discuss the simple reflex agent, the model-based reflex agent, the goal-based agent, the utility-based agent, and the learning agent.
The course is based on the textbook by Stuart Russell and Peter Norvig: Introduction to Artificial Intelligence, 3rd edition, 2012 or in the English version Artificial Intelligence - A Modern Approach.
The course is held in English language with German subtitles.
This course is part of the course series "Foundations of Artificial Intelligence I-V":
- Foundations of Artificial Intelligence I: Introduction to AI, Agents
- Foundations of Artificial Intelligence II: Search algorithms
- Foundations of Artificial Intelligence III: Logic and satisfiability
- Foundations of Artificial Intelligence IV: Knowledge representation
- Foundations of Artificial Intelligence V: Constraint solving problems
The single courses deal with different methodological complexes of AI.
Which topics will be covered?
- The beginnings of Artificial Intelligence
- Alan Turing and his seminal article «Can machines think?
- Symbolic and Subsymbolic AI
- Four possible directions of AI research
- The Turing Test
- A working definition for «Artificial Intelligence»
- History of AI
- The beginnings of AI (1943 - 1956)
- Early successes and enthusiasm (1956 – 1969)
- Steady progress with a dose of reality (1970 – 1985)
- The AI winter (1987–1993)
- Data-driven AI (since 2000)
- Selected current challenges of AI and the next decades of research
- Transfer and reinforcement learning
- Creativity and „magic“ during AI-based learning
- Limitations in the understanding of unstructured information
- Bias in data and automatic decisions
- Ethical questions
- The 4 big A of AI search and the US AI community roadmap
Module Intelligent Agents
- Metaphor of the rational agent
- The Rational Agent
- Modeling an Agent
- Performance Measure and Utility Function
- Properties of Agents and Environments
- The PEAS Description of an agent/environment system
- The Utility Function of an Agent
- Utility vs. Performance
- Properties of Environments
- Simple and Complex Environments
- Architectures of intelligent agents
- Simple Reflex agent
- Model-based Reflex agent
- Goal-based agent
- Utility-based agent
- Learning agent
What will I achieve?
By the end of the course, you‘ll be able to...
- reflect on the history of artificial intelligence and its current challenges,
- understand the basic design of intelligent systems based on the concept of the rational agent,
- participate in AI projects in practice.
Which prerequisites do I need to fulfill?