The subject starts with a description of problem solving methods by means of heuristic search. Therafter, various knowledge representation languages and inference methods for automatic problem solving. Representation in form of predicate logic, frames and semantic nets are treated, and connected to the main forms of reasoning - especially rule based reasoning. Furthermore, architectures that integrates various resoning methods, agent based architectures and architectures for interactive problem solving. Numerous applicaton examples are given to demonstrate the methods.
- historical perspective of AI and its foundations
- basic principles of AI toward problem solving inference, and knowledge representation
- knowledge based systems using logic
- uninformed and heuristics search methods, constraint satisfaction problems and methods, and adversarial search
- representation of planning problems and solution methods
- multiagent environments and game theory principles and some methods
- ethics related problems in AI
- Decide which types of intelligence and agents are needed in a certain type of environment and design the agent accordingly
- Design knowledge-based systems using the suitable type of representation, inference and problem solving method
- Be able to identify possible ethical problems for a given a problem General
Know AI's basis taken from logic and cognitive sciences.
