Description

 Understand the concepts and principles of reinforcement learning and decision-making.  Gain proficiency in applying reinforcement learning and decision-making algorithms to solve complex problems.  Develop the ability to analyze decision problems and make optimal choices under uncertainty.  Learn about advanced topics and recent research developments in reinforcement learning and decision-making.  Understand the fundamental concepts and theories of decision-making.  Gain proficiency in applying decision-making models and frameworks.  Develop critical thinking and analytical skills for making optimal decisions.  Learn about decision biases and heuristics that affect decision-making.

Program

Artificial Intelligence 132 CRs

Objectives

• This course provides an in-depth introduction to reinforcement learning, a subfield of machine learning. Students will learn about the fundamental concepts, algorithms, and applications of reinforcement learning. The course will cover both theoretical foundations and practical implementation techniques. This course also provides a comprehensive study of reinforcement learning and decision-making techniques. Students will learn about the principles, algorithms, and applications of both reinforcement learning and decision-making methods. The course also will cover theoretical foundations, practical implementation, and the integration of these techniques in real-world scenarios.