Courses:

Principles of Autonomy and Decision Making >> Content Detail



Lecture Notes



Lecture Notes

All notes are courtesy of the sources named and used with permission. Brian Williams' lectures will be noted with (BW), Paul Robertson's with (PR), Nick Roy's with (NR), and Charles Leiserson's with (CL).


Lec #TopicsLecture notes
1Principles of Autonomy and Decision Making - BW(PDF)
2A Very Brief Introduction to Java® - PR(PDF)
3Formulating Problem Solving as State Space Search - BW

Optional Lecture: More Fun with Java® - PR
(PDF 1 - 1.2 MB) (PDF 2)
4Problem Solving with Java® - PR(PDF)
5Asymptotic Analysis of Uninformed Search Methods - BW(PDF - 1.0 MB)
6Global Path-Planning via Optimal Search and Shortest Paths - BW(PDF)
7Roadmaps and Adversarial Games - BW(PDF)
8Solving Linear Programs using Simplex - PR(PDF)
9Kinodymanic Path-Planning using Linear Programs - PR(PDF)
10Formulating Visual Interpretation using Constraint Programming - BW(PDF)
11Solving Constraint Programs using Inference and Search - BW(PDF)
12Activity Planning and Plan Graphs - BW(PDF)
13Plan Extraction in Graph Plan - BW(PDF)
14Planning and Execution in a Changing World - BW(PDF)
15Modelling using Propositional Logic - BW(PDF)
16Propositional Satisfiability - BW(PDF)
17Entailment and Inference in Propositional Logic - BW(PDF)
18Model-Based Diagnosis and Conflict-directed Search - BW(PDF)
19Introduction to Probabilistic Reasoning - BW(PDF)
20Probabilistic State Estimation and Robot Localization - PR, BW(PDF 1) (PDF 2)
21Formulating Utility-based Agents using Markov Decision Processes - CL, BW(PDF 1) (PDF 2)
2216.413 Student Project Presentations
23Learning from Observations through Inductive Methods - NR(PDF)
24Learning from Observations through Statistical Methods - NR(PDF)
25Making Decisions through Finite Domain Constraint Optimization
26Final Exam Review(PDF 1) (PDF 2 - 2.5 MB)

 








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