2012 Courses

Prof. Barry G. Silverman, 120 Hayden Hall, (215) 573-8368
Office Hours: Tuesday and Thursday: 2 – 4 PM



ESE 308 Abstract

AGENT-Based Modeling & Simulation:

Artificial Life, Human Behavior, and Socio-Technical Systems

Classroom: Towne 305, Labs in Moore 100B


Agents are a new technique for trying to model, simulate, and understand systems that are ill-structured and whose mathematics is initially unknown and possibly unknowable. This approach allows the analyst to assemble models of agents and components where micro-decision rules may be understood; to bring the agents and components together as a system where macro-behavior then emerges; and to use that to empirically probe and improve understanding of the whole, the interrelations of the components, and synergies. This approach helps one explore parametrics, causality, and what-ifs about socio-technical systems (technologies that must support people, groups, crowds, organizations, and societies). It is applicable when trying to model and understand human behavior – consumers, investors, passengers, plant operators, patients, voters, political leaders, terrorists, and so on. This course will allow students to investigate and compare increasingly complex agent based paradigms along three lines – math foundations, heuristic algorithms/knowledge representations, and empirical science. The student will gain a toolbox and methodology for attempting to represent and study complex socio-technical systems. Prereqs: probability, Java or C programming, or equivalent.



Students taking this class will learn to:



Michael D. Resnik (1987)  Choices: An Introduction to Decision Theory.  Minneapolis: University of Minnesota Press.

Packet of Readings about Agent Based Modeling and Simulation




ESE 590 –Systems Methodology


Classroom: Moore 216 and Labs in Moore 100B

Professor: Dr. Barry G. Silverman, 120 Hayden Hall, (215) 573-8368


Catalog Description: This course covers the methodologies and techniques important to DESIGNING large complex, purposeful systems and to discovering policies that influence them throughout the stages of their lifecycle. The course focuses on hands-on synthetic thinking, where students assemble the big picture from modeling the individual actors, organizations, and artifacts in a socio-technical system of interest. This is the study of emergence of macro-behavior from the micro-decision making of the actors involved - to inquire into the design of a purposeful system, and to examine alternative futures that are ideal, yet affordable, sustainable, and workable. Specifically, the student learns systems theory, systems methodologies (design inquiry/learning systems, idealized design/interactive planning, and soft systems methodology/knowledge management), bottom up modeling (decision science, multi-attribute utility theory, affective reasoning, agent based modeling, simulated societies), and how to further research and apply the synthetic paradigm.

 Course Objectives: What you should know and skills you should have by the end of this course: