P657 : Multiagent Modeling of Social Behavior
Many significant forms of human social behavior arise not because of one individual's desires or decisions, but as an outcome of the interactions of multiple individuals, responding to their own goals and understandings of the situation. Examples include escalation of conflict, convergence of groups to premature consensus or "groupthink" and emergence of fads and fashions. Multiagent modeling aims at understanding such behaviors, by investigating the consequences of different assumptions about individual agents, agent interactions, and the surrounding environment. This course will focus on developing students? understanding of multiagent systems by analyzing examples in topic areas including collective search or problem solving, social influence, cooperation, and mate choice. Students will learn the Netlogo language and use it to produce a meaningful multiagent model as a term project.
Instructor: Prof. Eliot smith - firstname.lastname@example.org
Other Contact(s): Prof. Eliot smith - email@example.com
Algebra Required?: No.
Calculus Required?: No.
Day(s) per week offered: 1 day/week, no lab
Substantive Orientation: The course is appropriate for graduate students in psychology, cognitive science, or related fields who are interested in multiagent modeling, as well as for those interested in deepening their understanding of topics within social psychology.
Statistical Orientation: Modeling
Books used: Railsback & Grimm, Agent-based and individual-based modeling (Princeton).
Software Used: NetLogo
How the software is used: Programming
Problem Sets: Homeworks
Presentations: Term project and class presentations
Keywords: multiagent, modeling, social influence, collective search, cooperation, NetLogo