Complex systems theory

Complex adaptive system

A complex adaptive system is a system that is complex in that it is a dynamic network of interactions, but the behavior of the ensemble may not be predictable according to the behavior of the components. It is adaptive in that the individual and collective behavior mutate and self-organize corresponding to the change-initiating micro-event or collection of events. It is a "complex macroscopic collection" of relatively "similar and partially connected micro-structures" formed in order to adapt to the changing environment and increase their survivability as a macro-structure. The Complex Adaptive Systems approach builds on replicator dynamics. The study of complex adaptive systems, a subset of nonlinear dynamical systems, is an interdisciplinary matter that attempts to blend insights from the natural and social sciences to develop system-level models and insights that allow for heterogeneous agents, phase transition, and emergent behavior. (Wikipedia).

Complex adaptive system
Video thumbnail

Mathematical modeling of evolving systems

Discover the multidisciplinary nature of the dynamical principles at the core of complexity science. COURSE NUMBER: CAS 522 COURSE TITLE: Dynamical Systems LEVEL: Graduate SCHOOL: School of Complex Adaptive Systems INSTRUCTOR: Enrico Borriello MODE: Online SEMESTER: Fall 2021 SESSION:

From playlist What is complex systems science?

Video thumbnail

What Are Reactive Systems?

Reactive Systems use a high-performance software architecture. They are resilient under stress, and their reactive design allows them to scale elastically to meet demand. The reactive design approach allows the creation of more complex, more flexible systems and forms the basis for some of

From playlist Software Engineering

Video thumbnail

What Are Phased Arrays?

This video introduces the concept of phased arrays. An array refers to multiple sensors, arranged in some configuration, that act together to produce a desired sensor pattern. With a phased array, we can electronically steer that pattern without having to physically move the array simply b

From playlist Understanding Phased Array Systems and Beamforming

Video thumbnail

Swarms, Societies, and Superorganisms

How do we decompose the drivers of success and failure in complex living groups? COURSE NUMBER: CAS 503 COURSE TITLE: Fundamentals of Complex Systems Science: Collectives LEVEL: Graduate SCHOOL: School of Complex Adaptive Systems INSTRUCTOR: Bryan Daniels MODE: Online SEMESTER: Fall 202

From playlist What is complex systems science?

Video thumbnail

Humans and Our Environment – A Complex Relationship

This course is designed to highlight approaches that can help us understand the intricate relationships that form between humans and our environment. COURSE NUMBER: CAS 540 COURSE TITLE: Socio-Ecological Complex Systems LEVEL: Graduate SCHOOL: School of Complex Adaptive Systems INSTRUCT

From playlist What is complex systems science?

Video thumbnail

Stanford Seminar - Universal Intelligent Systems by 2030 - Carl Hewitt and John Perry

Carl Hewitt of MIT and John Perry of Stanford discuss Universal Intelligent Systems. This talk was given on January 5, 2022. Universal Intelligent Systems (UIS) will encompass everything manufactured and every sensed activity. Every device used at home and work will be included as well a

From playlist Stanford EE380-Colloquium on Computer Systems - Seminar Series

Video thumbnail

Discrete-Time Dynamical Systems

This video shows how discrete-time dynamical systems may be induced from continuous-time systems. https://www.eigensteve.com/

From playlist Data-Driven Dynamical Systems

Video thumbnail

David Woods Velocity NY 2014 Keynote: "The Mystery of Sustained Adaptability"

From the 2014 Velocity Conference in New York City. Click to watch our interview with David Woods: http://goo.gl/bm9iRi As technologies change and people adapt to take advantage of those technologies, we can contrast successful and unsuccessful cases of managing the complexity that resul

From playlist Velocity Conference 2014 (New York, NY)

Video thumbnail

David Woods (Ohio State University) Interview - Velocity NY 2014

From the 2014 Velocity Conference in New York City, the Ohio State University professor expands on his keynote about sustained adaptability. Click to watch David Woods's keynote address: http://goo.gl/l5tB8a About David Woods (Professor, Ohio State University): David Woods is currently t

From playlist Velocity Conference 2014 (New York, NY)

Video thumbnail

A Real World Example of BDD

Behavior Driven Development (BDD) is a great way to organise your development. Creating Executable Specifications helps us to guide our work, but what does that look like in the real world on a real project delivering real software? In this episode, Dave Farley shows some real-world BDD ex

From playlist Case Studies

Video thumbnail

Stanford Seminar: Expert Crowdsourcing with Flash Teams and Organizations

Daniela Retelny Stanford University Online crowdsourcing marketplaces provide access to millions of individuals with a range of expertise and experiences. To date, however, most research has focused on microtask platforms, such as Amazon Mechanical Turk. While microtask platforms have ena

From playlist Stanford Seminars

Video thumbnail

DDPS | Towards Robust, Accurate & Tractable Reduced-Order Models

Talk Abstract This talk presents advances towards the development of effective projection-based reduced order models (ROMs) for complex multi-scale multi-physics problems. As a representative application, we consider combustion dynamics in a rocket engine, which is characterized by the c

From playlist Data-driven Physical Simulations (DDPS) Seminar Series

Video thumbnail

Urban Traffic and Complex Systems

Carlos Gershenson, a computer scientist and complexity researcher at the National Autonomous University of Mexico, answers questions about how principles of adaptation and self-organization can help transportation systems beat traffic jams and other urban mobility problems. Read the full i

From playlist Inside the Mind of a Scientist

Video thumbnail

Can machines be emotionally intelligent? - with Hatice Gunes

Do machines need emotional intelligence? And how can we create technology that behaves in a socio-emotionally intelligent way? Watch the Q&A here: https://youtu.be/_IiyTD0Ogyc Subscribe for regular science videos: http://bit.ly/RiSubscRibe Join Hatice Gunes as she explains why socio-emot

From playlist Computing/Tech/Engineering

Video thumbnail

What are Scientific Breakthroughs in Biology? | Episode 2104 | Closer To Truth

What is the world fundamentally, deeply made of? What is life? We are always searching for Scientific Breakthroughs: those leaps in knowledge and jumps in understanding that change how we see the world. Now, we focus on Biology. What are Scientific Breakthroughs in Biology? Featuring inte

From playlist Closer To Truth | Season 21

Video thumbnail

Velocity NY 2013: Richard Cook, "Resilience In Complex Adaptive Systems"

http://velocityconf.com/velocityny2013/public/schedule/detail/31784 Resilience In Complex Adaptive Systems: Operating At The Edge Of Failure Systems seem to run at the very edge of failure much of the time. The combination of high workload, limited resources, pressure for additional feat

From playlist Velocity Conference 2013 (New York, NY)

Video thumbnail

Stochastic Tipping Points in Optimal Tumor Evasion and Adaptation Induced....by Jason George

PROGRAM TIPPING POINTS IN COMPLEX SYSTEMS (HYBRID) ORGANIZERS: Partha Sharathi Dutta (IIT Ropar, India), Vishwesha Guttal (IISc, India), Mohit Kumar Jolly (IISc, India) and Sudipta Kumar Sinha (IIT Ropar, India) DATE: 19 September 2022 to 30 September 2022 VENUE: Ramanujan Lecture Hall an

From playlist TIPPING POINTS IN COMPLEX SYSTEMS (HYBRID, 2022)

Video thumbnail

System of Equations with Three Equations and Three Variables

Please Subscribe here, thank you!!! https://goo.gl/JQ8Nys System of Equations with Three Equations and Three Variables

From playlist Systems of Equations

Related pages

Complexity | Mode (statistics) | Differential equation | Skewness | Dynamic network analysis | Complex system | Computational sociology | Swarm Development Group | John Henry Holland | Complex network | Sampling bias | Econophysics | Game theory | Variance | Random walk | Open system (systems theory) | Phase transition | Chaos theory | Artificial life | Mean-field game theory | Systems theory | Viability theory | Agent-based model | Emergence | Non-equilibrium thermodynamics | Dual-phase evolution | Self-similarity