| 1 |
Introduction and Scope |
Artificial Intelligence (MIT) |
MIT |
Applied Sciences |
| 2 |
Reasoning Goal Trees and Problem Solving |
Artificial Intelligence (MIT) |
MIT |
Applied Sciences |
| 3 |
Reasoning Goal Trees and Rule-Based Expert Systems |
Artificial Intelligence (MIT) |
MIT |
Applied Sciences |
| 4 |
Search Depth-First, Hill Climbing, Beam |
Artificial Intelligence (MIT) |
MIT |
Applied Sciences |
| 5 |
Search Optimal, Branch and Bound, A* |
Artificial Intelligence (MIT) |
MIT |
Applied Sciences |
| 6 |
Search Games, Minimax, and Alpha-Beta |
Artificial Intelligence (MIT) |
MIT |
Applied Sciences |
| 7 |
Constraints Interpreting Line Drawings |
Artificial Intelligence (MIT) |
MIT |
Applied Sciences |
| 8 |
Constraints Search, Domain Reduction |
Artificial Intelligence (MIT) |
MIT |
Applied Sciences |
| 9 |
Constraints Visual Object Recognition |
Artificial Intelligence (MIT) |
MIT |
Applied Sciences |
| 10 |
Introduction to Learning, Nearest Neighbors |
Artificial Intelligence (MIT) |
MIT |
Applied Sciences |
| 11 |
Learning Identification Trees, Disorder |
Artificial Intelligence (MIT) |
MIT |
Applied Sciences |
| 12 |
Neural Nets |
Artificial Intelligence (MIT) |
MIT |
Applied Sciences |
| 13 |
Deep Neural Nets |
Artificial Intelligence (MIT) |
MIT |
Applied Sciences |
| 14 |
Learning Genetic Algorithms |
Artificial Intelligence (MIT) |
MIT |
Applied Sciences |
| 15 |
Learning Sparse Spaces, Phonology |
Artificial Intelligence (MIT) |
MIT |
Applied Sciences |
| 16 |
Learning Near Felicity Conditions |
Artificial Intelligence (MIT) |
MIT |
Applied Sciences |
| 17 |
Learning Support Vector Machines |
Artificial Intelligence (MIT) |
MIT |
Applied Sciences |
| 18 |
Learning Boosting |
Artificial Intelligence (MIT) |
MIT |
Applied Sciences |
| 19 |
Representations Classes, Trajectories, Transitions |
Artificial Intelligence (MIT) |
MIT |
Applied Sciences |
| 20 |
Architectures GPS, SOAR, Subsumption, Society of Mind |
Artificial Intelligence (MIT) |
MIT |
Applied Sciences |
| 21 |
Probabilistic Inference I |
Artificial Intelligence (MIT) |
MIT |
Applied Sciences |
| 22 |
Probabilistic Inference II |
Artificial Intelligence (MIT) |
MIT |
Applied Sciences |
| 23 |
Model Merging, Cross-Modal Coupling, Course Summary |
Artificial Intelligence (MIT) |
MIT |
Applied Sciences |
| 24 |
Mega-R1. Rule-Based Systems |
Artificial Intelligence (MIT) |
MIT |
Applied Sciences |
| 25 |
Mega-R2. Basic Search, Optimal Search |
Artificial Intelligence (MIT) |
MIT |
Applied Sciences |
SEARCH COURSES
