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Course Outline

The Evolution of Artificial Intelligence

  • Intelligent Agents

Problem-Solving Techniques

  • Search-Based Problem Solving
  • Advances Beyond Classical Search
  • Adversarial Search Strategies
  • Constraint Satisfaction Problems

Knowledge and Logical Reasoning

  • Logical Agents
  • First-Order Logic
  • Inference Methods in First-Order Logic
  • Classical Planning
  • Planning and Action in Real-World Scenarios
  • Representing Knowledge

Reasoning with Uncertain Information

  • Measuring Uncertainty
  • Probabilistic Reasoning
  • Time-Series Probabilistic Reasoning
  • Simple Decision-Making Processes
  • Complex Decision-Making Processes

Machine Learning

  • Learning from Examples
  • Knowledge Integration in Learning
  • Learning Probabilistic Models
  • Reinforcement Learning

Communication, Perception, and Action

  • Natural Language Processing
  • Using Natural Language for Communication
  • Perception Systems
  • Robotics

Conclusions

  • Philosophical Underpinnings
  • Current State and Future of AI

Requirements

A basic understanding of computing, biology, mathematics, and physics

 7 Hours

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