Artificial Intelligence: A Modern Approach – Prentice Hall series in artificial intelligence, 2nd Edition

Artificial Intelligence: A Modern Approach – Prentice Hall series in artificial intelligence, 2nd Edition Description

Artificial Intelligence: A Modern Approach – Prentice Hall series in artificial intelligence, 2nd Edition provides new updates to numerous areas such as constraint satisfaction, fast propositional inference, Internet agents, planning graphs, exact probabilistic inference, Kalman filters, Markov Chain Monte Carlo techniques, ensemble learning methods, statistical learning, probabilistic robotics, probabilistic natural language models, and ethical aspects of AI.

Here’s what you will learn in this course:

• ARTIFICIAL INTELLIGENCE.
  • Introduction.
  • Intelligent Agents.
• PROBLEM-SOLVING.
  • Solving Problems by Searching.
  • Informed Search and Exploration.
  • Constraint Satisfaction Problems.
  • Adversarial Search.
• KNOWLEDGE AND REASONING.
  • Logical Agents.
  • First-Order Logic.
  • Inference in First-Order Logic.
  • Knowledge Representation.
• PLANNING.
  • Planning.
  • Planning and Acting in the Read World.
• UNCERTAIN KNOWLEDGE AND REASONING.
  • Uncertainty.
  • Probabilistic Reasoning Systems.
  • Probabilistic Reasoning Over Time.
  • Making Simple Decisions.
  • Making Complex Decisions.
• LEARNING.
  • Learning from Observations.
  • Knowledge in Learning.
  • Statistical Learning Methods.
  • Reinforcement Learning.
• COMMUNICATING, PERCEIVING, AND ACTING.
  • Agents that Communicate.
  • Text Processing in the Large.
  • Perception.
  • Robotics.
• CONCLUSIONS.
  • Philosophical Foundations.
  • AI: Present and Future.