Actions

Complex Systems Winter School 2015-Faculty: Difference between revisions

From Santa Fe Institute Events Wiki

No edit summary
No edit summary
Line 62: Line 62:
<br>
<br>
These lectures will provide an introduction to agent-based computational modeling, drawing on applications in economics and finance. The first lecture will focus on the manner in which decentralized, uncoordinated choices can give rise to emergent properties such as residential segregation. The second and third lectures will examine financial markets, with a focus on how asset price dynamics depend on the composition of trading strategies, and how the composition of strategies itself evolves under pressure of differential profitability.
These lectures will provide an introduction to agent-based computational modeling, drawing on applications in economics and finance. The first lecture will focus on the manner in which decentralized, uncoordinated choices can give rise to emergent properties such as residential segregation. The second and third lectures will examine financial markets, with a focus on how asset price dynamics depend on the composition of trading strategies, and how the composition of strategies itself evolves under pressure of differential profitability.
<br>
<br>
[[Image:sitsinha.jpg|150px|{border}]]<br>
[http://www.imsc.res.in/~sitabhra/ Sitabhra Sinha], '''Complexity in physiological systems'''<br>
<br>
<br>
<br>
<br>

Revision as of 15:22, 17 July 2015

Complex Systems Winter School 2015


Program Director


{border}
Somdatta Sinha, Program Director

Lecturers and Faculty


{border}
Tanmoy Bhattacharya, Theories and Treatment of Infectious Disease


{border}
Liz Bradley, Nonlinear Dynamics


{border}
Anirban Chakraborti, Econophysics

Lecture 1: Kinetic exchange models in complex socio-economic systems
Lectire 2: Statistical mechanics of competitive resource allocation: El Farol Bar to Kolkata Paise Restaurant


{border}
Arkadev Chattopadhyay , Computational Complexity


{border}
Aaron Clauset, Four Lectures on Network Science

Network science is a thriving cross-disciplinary domain focused on the representation, analysis and modeling of complex social, biological and technological systems as networks or graphs. These four lectures will provide a compact introduction to the modern study of network science. We will examine techniques for analyzing and modeling the structure and dynamics of complex networks, and we will cover a broad selection of the core concepts in the field. Some emphasis will be placed on statistical algorithms and methods, and on model interpretation and real data. Applications will be drawn from computational biology and computational social science.

{border}
Simon DeDeo, Cognitive Science and Social Minds


{border}
Laurent Hebert-Dufresne, Statistical Physics and Complex Networks


{border}
Eric Libby Microbial Ecology


{border}
Olé Peters, Non-Ergodic Economics


{border}
Eleanor Power, Social Science

Social theory, social complexity, and social networks

What happens when our complex systems involve actors that are not cellular automatons or microbes, but conscious, reflective humans? when they have some awareness of what the outcomes of their actions might be, a sense of their position relative to others, and a representation of the larger social entities of which they are a part? In order to understand human social complexity, we need to understand something about how humans operate. To that end, we will first go over some of the fundamentals of social theory, looking at how various theorists have understood how individual action both shapes, and is shaped by, social structure. Having understood some of the critical dynamics of social interaction, in lecture two we will grapple with perhaps a more fundamental topic: the emergence of human social complexity. How can we explain the origins of sedentism? the domestication of plants and animals? the development of social and political institutions (marriage, kinship, religion, property rights)? the advent of state society? This will have us turn to the archaeological record to study some of the crucial transitions in human history. In the final lecture, we will discuss some of the contemporary approaches to these questions of social complexity. We will focus in particular on one of the most promising methodological tools being used today: social network analysis. Focusing on some examples of current scholarship, we will see how some of these fundamental questions of human sociality and complexity are shaped into meaningful, and feasible, research questions.

{border}
Rajiv Sethi, Agent-Based Computational Economics

These lectures will provide an introduction to agent-based computational modeling, drawing on applications in economics and finance. The first lecture will focus on the manner in which decentralized, uncoordinated choices can give rise to emergent properties such as residential segregation. The second and third lectures will examine financial markets, with a focus on how asset price dynamics depend on the composition of trading strategies, and how the composition of strategies itself evolves under pressure of differential profitability.

{border}
Sitabhra Sinha, Complexity in physiological systems


{border}
Andreas Wagner, Evolution and genotype networks

After a brief survey of important milestones in the history of evolutionary biology, these lectures will turn to the most fundamental problem of the field, namely how evolution creates new and beneficial features of organisms. This “innovation problem” has recently been tackled in different classes of complex molecular systems, including chemical reaction networks in metabolism, regulatory gene circuits, as well as protein and RNA macromolecules. I will discuss these efforts, the progress that has been made, and introduce the important role genotype networks play for innovation in all these systems. I will also touch upon other important tensions in modern evolutionary biology that relate to the innovation question, such as that between neutral and selected change, as well as that between a system’s robustness and its innovation ability. Time permitting, I will also discuss how recent insights into the innovation problem in biology could apply to technological evolution.


Staff

{border}
Juniper Lovato, Manager, Schools, Residencies, and Community Outreach, Santa Fe Institute