This course, CPSC 532A, introduces students to the mathematical and computational foundations of multiagent systems (MAS), focusing on game-theoretic analysis of systems where agents may not act cooperatively. The course emphasizes student participation through seminar-style discussions and traditional lectures. It concludes with a research project where students survey existing literature and explore open research questions. The course covers topics at the intersection of economic theory and computer science, including games (normal-form, extensive-form, repeated, stochastic, Bayesian), computation of game-theoretic solution concepts, mechanism design, single-good auctions, and combinatorial auctions. No formal prerequisites are required, but students should have basic knowledge of probability theory, computational complexity, and combinatorial optimization. The course involves reading papers, writing a survey or research paper, and presenting findings to the class. Academic honesty is strictly enforced, with plagiarism considered a serious offense. Students must sign an honor code statement acknowledging acceptable forms of collaboration and reference to non-course materials. The grading scheme includes three or four assignments, with the last one weighted more heavily. Students are given three late days for assignments, but not for the final project. The final project requires students to write a paper on a topic in MAS, submit a one-page outline, and undergo peer review. Topics can range from surveys of subareas to comparative studies of influential papers. The course uses a new text in electronic form, which will be updated throughout the year. Students are encouraged to print individual chapters as they are covered. The course explores different levels of agency, including single-agent, distributed single-agent, and multiple agents. It distinguishes these agents by their autonomy, asymmetric information, and ability to choose how to share information. The course also covers disciplines contributing to MAS, including computer science, economics, operations research, analytic philosophy, and linguistics. The theory of MAS focuses on quantitative, motivational, individual-based, strategic approaches, though other approaches are briefly discussed.This course, CPSC 532A, introduces students to the mathematical and computational foundations of multiagent systems (MAS), focusing on game-theoretic analysis of systems where agents may not act cooperatively. The course emphasizes student participation through seminar-style discussions and traditional lectures. It concludes with a research project where students survey existing literature and explore open research questions. The course covers topics at the intersection of economic theory and computer science, including games (normal-form, extensive-form, repeated, stochastic, Bayesian), computation of game-theoretic solution concepts, mechanism design, single-good auctions, and combinatorial auctions. No formal prerequisites are required, but students should have basic knowledge of probability theory, computational complexity, and combinatorial optimization. The course involves reading papers, writing a survey or research paper, and presenting findings to the class. Academic honesty is strictly enforced, with plagiarism considered a serious offense. Students must sign an honor code statement acknowledging acceptable forms of collaboration and reference to non-course materials. The grading scheme includes three or four assignments, with the last one weighted more heavily. Students are given three late days for assignments, but not for the final project. The final project requires students to write a paper on a topic in MAS, submit a one-page outline, and undergo peer review. Topics can range from surveys of subareas to comparative studies of influential papers. The course uses a new text in electronic form, which will be updated throughout the year. Students are encouraged to print individual chapters as they are covered. The course explores different levels of agency, including single-agent, distributed single-agent, and multiple agents. It distinguishes these agents by their autonomy, asymmetric information, and ability to choose how to share information. The course also covers disciplines contributing to MAS, including computer science, economics, operations research, analytic philosophy, and linguistics. The theory of MAS focuses on quantitative, motivational, individual-based, strategic approaches, though other approaches are briefly discussed.