ECE 5242

ECE 5242

Course information provided by the 2018-2019 Catalog.

How can intelligent machines perceive, make decisions, and execute their plans in an uncertain, dynamic world? This course will cover algorithms for robotic perception, planning, and control with a focus on real-time adaptation and learning. Students should have prior experience with methods in signal processing and machine learning. Topics covered include probabilistic methods for scene segmentation, multimodal sensory integration, latent variable models for dynamical systems, path planning, and reinforcement learning for motor control.


Prerequisites/Corequisites Recommend Prerequisite: CS 5785.

Permission Note Enrollment limited to: students at Cornell Tech.

When Offered Spring.

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Syllabi: none
  •   Regular Academic Session. 

  • 3 Credits Graded

  • 17481 ECE 5242   LEC 001

  • Instruction Mode: In Person

    Taught in NYC. Enrollment limited to Cornell Tech Students.