CMPSC 303 · Fall 2026 · Allegheny College
Artificial Intelligence
From search and reasoning under uncertainty to agents that plan, use tools, and coordinate with each other: a hands-on tour of how intelligent systems are built, and what it means to build them responsibly.
What you will build
Weeks 2–5
Agents & Search
Implement intelligent agents from scratch, then teach them to search, culminating in a game-playing agent project.
Weeks 6–9
Reasoning & Uncertainty
Logic-based agents, Bayesian reasoning, and a hands-on look at algorithmic bias and model explainability: evaluating AI systems, not just building them.
Weeks 10–15
Agentic AI
Tool use, planning loops, memory & retrieval, multiagent coordination, and what changes when an agent has to run on constrained hardware.
Course learning outcomes
- Correctly implement an intelligent agent and accurately describe its properties.
- Correctly apply search algorithms to solve an agent-based problem.
- Design, implement, and assess an intelligent system for various artificial intelligence applications.
- Correctly explain and justify how a problem could be solved through the use of supervised, unsupervised, and/or reinforcement machine learning algorithms.
- Evaluate intelligent systems while considering their social, political, and ethical implications and communicate their outcomes in both written and oral forms.