Systems Science Friday Noon Seminar Series



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15-minute presentations on the following three topics:

I. Live Group Simulations Promote Learning of Systems Concepts
Systems concepts such as attractors, bifurcation, chaotic behavior, and emergence may be hard for learners to grasp. Even when they follow a lecture or demonstration, they may wonder about practical use. How might we more effectively convey systems concepts? For fourteen years, I have used group activities to stimulate learning of systems concepts and multi-agent behavior in general. The activity might involve as few as ten participants or 150-plus. Whether you have 10 minutes, 90 minutes, or 4 weeks, there is an effective simulation. I will discuss principles of effective simulation and briefly describe three such simulations. The first example, a 10-minute simulation, relies on a simple algorithm where students sit and stand in class based on certain conditions. The second takes students outside to follow one of ten simple rules, with fascinating results that show definite, repeatable patterns even as each simulation generates a unique historical path. Finally, I will showcase the Tavistock method, a 4-week small group activity that highlights numerous concepts, including the value of viewing groups as living systems and how a unique culture emerges from easily stated, though paradoxical, challenges. Finally, I will highlight the value of physical props and use of physical space, with a conjecture: emergence occurs most in multi-agent systems located in a space.

II. Trait-Based Meme Diffusion Through Multi-Agent Friendship Networks
How might we accurately and simply model the diffusion of information through a social system? Classic diffusion assumes a homogeneous population and relies on a single equation of growth with a coefficient. In contrast, multi-agent simulation affords a heterogeneous population where some agents are more or less likely to notice, accept or share a meme. The multi-agent approach reproduces real-world oddities in diffusion. But what about the meme itself? As observers or even policymakers, we are unlikely to notably alter people’s preferences. Thus, we might wish to know how to tailor a meme to increase its acceptance within a population. Doing so requires we “look inside” the meme, at its elements, rather than treating it as an atomic unit. But how can we simply characterize a meme in a way that’s relevant to agents? I will show a working simulation that addresses this challenge. Specifically, the simulation generates a large population of heterogeneous agents with traits based on demographic trends; then, it links those agents into a friendship network based on trait compatibility; and finally, it introduces a set of example memes that are characterized in terms of the agents‘ own traits, with acceptance and transference handled in a fuzzy way.

III. Nonlinear Training Scenarios Assess Decision-Making in Context
Engaging learners in a design process often asks them to consider questions they might miss in a traditional learning environment. Design also helps students internalize material and help them “reality test” their ideas. Although engineering students--and fine arts students--are used to design, many other students from the physical and social sciences and humanities are not. How can we engage them to internalize design concepts. Design often invokes many questions. What tangible goals are we striving to meet? What resources do we need, and how to qualify or budget resource use? Who is using the resulting design? How well will the result work for them? How might we solicit and integrate feedback? What is our creative process to ensure a best possible result? Are there best-practices and reliable principles? And many more questions. I focus on interactive fiction training scenarios because this blends topics that students from across the academic disciplines are familiar with, from virtual cultural explorations to medical problem solving. I also focus on decision-making in context because students in many disciplines will go on to decision making positions in their careers and will lack preparation to understand how their decisions will play out in unexpected, nonlinear ways that may vary with context and/or defy expectations.

Biographical Information

Dario is a founder of UCLA’s Human Complex Systems degree program, winner of UCLA’s annual Distinguished Teaching award, and author/coauthor of numerous books including “Neuroscience of Personality”. He received his degree from SUNY Binghamton in Systems Science. His undergraduate degree is Aerospace Engineering from USC. Dario is also the founder and CEO of Radiance House media and books.


System theory -- Study and teaching (Higher), Concepts, Group work in education, Activity programs in education, Information modeling -- Simulation methods, Design -- Study and teaching (Higher) -- Social aspects


Higher Education | Social and Philosophical Foundations of Education

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Instructional Practices for Teaching Systems Concepts