AGENTIC AI SYSTEMS

Catalog description

This course offers an in‑depth exploration of topics in agentic artificial intelligence (AI) systems. Students critically examine contemporary research on cognitive and reactive agent architectures, multi‑agent reinforcement learning, neuro‑symbolic and hybrid agents, integration of large language models into autonomous agents, evaluation methodologies, and ethical considerations. Through a combination of lectures, student‑led paper presentations, assignments, and a research project, students develop the skills needed to design, implement, and evaluate agentic AI systems. (3 credits) fall, spring, summer