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This course introduces students to the basic knowledge representation, problem solving, and learning methods of artificial intelligence.

0

4

English

English [CC]

FREE

Description

Upon completion of 6.034, students should be able to develop intelligent systems by assembling solutions to concrete computational problems; understand the role of knowledge representation, problem solving, and learning in intelligent-system engineering; and appreciate the role of problem solving, vision, and language in understanding human intelligence from a computational perspective

Course content

  • Introduction and Scope Unlimited
  • Reasoning: Goal Trees and Problem Solving Unlimited
  • Reasoning: Goal Trees and Rule-Based Expert Systems Unlimited
  • Search: Depth-First, Hill Climbing, Beam Unlimited
  • Search: Optimal, Branch and Bound, A* Unlimited
  • Search: Games, Minimax, and Alpha-Beta Unlimited
  • Constraints: Interpreting Line Drawings Unlimited
  • Constraints: Search, Domain Reduction Unlimited
  • Constraints: Visual Object Recognition Unlimited
  • Introduction to Learning, Nearest Neighbors Unlimited
  • Learning: Identification Trees, Disorder Unlimited
  • Neural Nets Unlimited
  • Deep Neural Nets Unlimited
  • Learning: Genetic Algorithms Unlimited
  • Learning: Sparse Spaces, Phonology Unlimited
  • Learning: Near Misses, Felicity Conditions Unlimited
  • Learning: Support Vector Machines Unlimited
  • Learning: Boosting Unlimited
  • Representations: Classes, Trajectories, Transitions Unlimited
  • Architectures: GPS, SOAR, Subsumption, Society of Mind Unlimited
  • Probabilistic Inference I Unlimited
  • Probabilistic Inference II Unlimited
  • Model Merging, Cross-Modal Coupling, Course Summary Unlimited

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Instructor

Massachusetts Institute of Technology
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