Basic Information
Computational Foundations of Automated Planning. Classical Planning With No Uncertainty# Optimal and Semi-optimal Planning, State-space And Plan-space Search Algorithms, Automatic Construction of Search Heuristics, Planning As Iterative Constraint Satisfaction. Extensions to Planning With Quantitiative Resources and Qualitative/ Stochastic Uncertainty. Application of Automated Planning In Autonomous Software and Hardware Systems.
Faculty: Data and Decision Sciences
|Graduate Studies
Pre-required courses
96210 - Foundations and Applications of Artificial Intelligence or 236501 - Introduction to Artificial Intelligence
Semestrial Information
Weekly Hours
2.5 Academic Credit • 2 Lecture Hours • 1 Project Hours
Responsible(s)
Erez Karpas
Registration Groups
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Weekly Hours
2.5 Academic Credit • 2 Lecture Hours • 1 Project Hours
Responsible(s)
Erez Karpas
Registration Groups
|
|
Weekly Hours
2.5 Academic Credit • 2 Lecture Hours • 1 Project Hours
Registration Groups
|
|