Artificial Intelligence

Catalog description

Artificial Intelligence (AI) is an interdisciplinary field, integrating knowledge and methods from computer science, mathematics, philosophy, psychology, economics, neuroscience, linguistics, and biology. Intelligent agents mimic cognitive functions to implement intelligent behaviors such as perception, reasoning, communication, and acting in symbolic and computational models. AI is used in a wide range of narrow applications, from medical diagnosis to speech recognition to bot control. The autonomous single, multiple, and adversarial agents that students build in this course will support fully observable and partially observable decisions in both deterministic and stochastic environments. Topics covered include search, constraint satisfaction, Markov decision processes, planning, knowledge representation, reasoning under uncertainty, graphical models, and reinforcement learning. The techniques and technologies mastered here will provide the foundational knowledge for the ongoing study and application of AI in other applications across practice areas. Prerequisite(s): Data Acquisition and Management; Computational Statistics and Probability.