Schedule

No lab this week.

Welcome to the course. What is AI?

• Set up your tools: uv, Python, and an editor

Intelligent Agents I: the PEAS framework, agent types, and environment properties.

• Challenge 1: simple reflex agent

Labor Day Mon Sep 7 (no class)

Intelligent Agents II and Search: agent architecture patterns and uninformed search.

• Challenge 2: Kevin Bacon or maze (BFS)
• Briefing 1: agents in the wild

Search: informed search and an introduction to adversarial search.

• Challenge 3: A* implementation

Adversarial search: alpha-beta pruning; game design as a search problem.

• Project 1 (Search & Games) begins: team game-playing challenge

Knowledge & Logic: propositional logic, knowledge representation, logic-based agents.

• Challenge 4: Clue/Mastermind-style reasoning
• Briefing 2: the state of the art
• Project 1 demo

Fall Break Thu Oct 8–Sun Oct 11 (no Thursday class)

Uncertainty I: probability, Bayes’ rule.

Uncertainty II: Bayesian networks; brief intro to Markov chains and HMMs.

• Challenge 5: the autonomous-vehicle Bayes’-rule dilemma

Midterm grades available Mon Oct 19

A light conceptual bridge into machine learning, plus hands-on algorithmic bias and explainability tools.

• Challenge 6: algorithmic bias & explainability activity
• Briefing 3: AI systems and the people they affect
• Project 1 due, with code review

Agentic Frameworks & Tool Use I: what makes a system "agentic," planning loops, function/tool-calling mechanics.

• Challenge 7: build a simple tool-using agent
• Briefing 4 interviews begin: your assigned faculty or staff contact goes out this week

All-College Programming Day Tue Nov 3 (no class or lab)

Agentic Frameworks & Tool Use II: orchestration patterns, a framework survey, guardrails and error handling in tool loops.

Agent Design & Architecture and Memory I: planning modules, control loops, context windows, and short vs. long-term memory.

• Project 2 (Agentic Tool-Use & Memory) begins: individual
• Briefing 4: Allegheny AI Perspectives

Memory & Retrieval II: retrieval-augmented generation, vector stores. Multiagent Systems I: communication protocols, cooperative vs. competitive agents.

• Challenge 8: memory/retrieval exercise
• Project 2 pitch

Thanksgiving Break Wed Nov 25–Sun Nov 29 (no Thursday class)

Multiagent Systems II: coordination case studies, negotiation, emergent behavior.

• Challenge 9: multiagent case study

Restricted and edge hardware, plus course wrap-up.

• Project 2 due, with code review
• Briefing 5: ethics, policy, and where this is going

Final Capstone presentations: student’s choice of a multiagent coordination system or an agent adapted for constrained hardware.

• Final Capstone due, with presentation and code review