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Artificial Intelligence

Intro to Artificial Intelligence
- What is AI
- Introduction to AI Level
- A Brief History of Artificial Intelligence
- Type of Artificial Intelligence
- Where is AI used? Example
- Why is AI booming now?
- Setting Up Environment with Anaconda
Logic & Theorem Proving
- Review prepositional & predicate Calculus
- Resolution
Production Rules
- Procedural versus declarative knowledge
- Forward versus backward reasoning
- Matching
- Control Knowledge
Statistical Reasoning
- Classical logic versus nonmonotonic logic
- Default logic
- Circumscription
- Fuzzy Logic
- Typicality
- Levels of confidence
- Baye’s Theorem
- Dempster-Shafer theory of evidence
Slot & Filter Structures
- Semantic nets
- Frames
- Scripts

Learning
- Rote Learning
- Learning by taking advice
- Explanation based learning
- Discovery
- Analogy
Computer Vision
- Defining the problem
- Overview of solution: Marr’s Theory
- Early processing: Gray level primal sketch
- Primal sketch to 2.5D sketch
- Late processing: 2.5D sketch to 3D sketch
Natural Language Processing
- Defining the problem
- Overview of solution
- Syntactic Analysis: Context-free grammars
- Transformational grammars
- Parsing: Top-down, bottom-up & chart parsing
- Semantics: Thematic roles, Aktionsart, Coercion, Cospecification, Extended reasoning with KB
- Discourse & Pragmatic Processing: Modelling
Connectionism
- Biological basis of connections
- Historical background to connections
- McCulloch & Pits formal neuron, Hebb's learning rule, Rosenblatt's perception
- Associations
- Hopfield Networks
- Backpropagation
- Connectionist representations & representational adequacy
Expert System in AI
- What is an Expert System?
- Characteristic of Expert System
- Components of the expert system
- Other key terms used in Expert systems
- Participant in Expert Systems Development
- Conventional System vs. Expert system
- Human expert vs. expert system
- Benefits of expert systems
- Limitations of the expert system
- Applications of expert systems