Course announcement: Autonomous Decision Making in the Real World, ABE 598

Autonomous Decision Making in the Real World,

ABE 598, Spring 2019 (Ceramics 218)

Instructor: Dr. Girish Chowdhary (girishc@illinois.edu)

Then Autonomous Decision Making is the course for you. The course is specifically

designed to accomdate beginners as well as experts. We will survey state-of-the-art

techniques in autonomy, machine learning, and decision making, including:

• Introduction to automatic reasoning

• Applied Machine learning:

o Supervised Learning:

(Deep/Convolutional) Neural Networks for classification, Gaussian processes

o Unsupervised Learning: Clustering using K-means, Dirichlet Processes, DNNs

o Mixture modeling: Hierarchic Bayesian models, Hidden Markov Models

o Dynamic ML: (deep) Recurrent Neural Networks, Evolving Gaussian Processes

• Applied Sequential decision making:

o Markov Decision Processes: Value/Policy iteration, trajectory based methods

o Reinforcement Learning: SARSA, Qlearning Model based methods

o Multi-agent and partially observed MDPs

• Software implementation of autonomy algorithms on resource-constrained hardware

This is a project based course. Students can choose final-projects from:

- Applications to defense, agriculture, and asset monitoring

- Robotics and autonomous vehicle systems

- Other projects related to your research

Prerequisites: Graduate Standing or Consent of Instructor.

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