Reference books from Suki
Steven Johnson, “Introduction,” “Street Level,” and excerpts from “Pattern Match” and “See What Happens,” from Emergence: The Connected Lives of Ants, Brains, Cities, and Software, Scribner, 2001
D’Arcy Wentworth Thompson, On Growth and Form
Phillip Ball, The Self-Made Tapestry
Sanford Kwinter, ‘Soft Systems’, Culture Lab 1, Brian Boigon ed., (Princeton, 1993), pp. 208-227
Thanks Lyds!!
Stratus Project
The Stratus Project develops a kinetic interior envelope, seemingly alive with sensors and intelligence, set into motion based on sensory input to affect the atmosphere that it surrounds, and in continual information exchange and dialogue with breather and environment. The fully realized system will develop a series of immersive layers, from a sensing, breathing and energy scavenging ground plane to a deep enveloping soffit, considering the material design of both that which is sensed – surfaces, atmospheres, thermal gradients and light – and that which lies beyond our sensory capabilities – aerosols, energies, transmission and radiation waves.
Research Through Making – Stratus Project from Taubman College on Vimeo.
MEASURING COLLECTIVE INTELLIGENCE (Experiment)
Thomas W. Malone (MIT), Stephen Kosslyn (Harvard), Anita Williams Woolley (Carnegie Mellon), Christopher Chabris (Union College) and Nada Hashmi (MIT)
Intelligence tests can predict the performance of individuals across a broad range of tasks. Imagine if we had an instrument that could predict the performance of groups—combinations of people assisted by computers, telecommunications links, and other man-made devices—across a range of relevant tasks. And imagine that this instrument would allow us to test whether efforts to improve performance on key tasks actually succeeded in making a group “smarter.”
The goal of the Measuring Collective Intelligence project is to find out whether such an instrument is feasible, and if so, to develop and test it, and then to use it to assess the effectiveness of interventions designed to enhance performance. The project will focus in three main areas.
- First, we will use what is already known about measuring individual intelligence to generate, by analogy, ideas about new ways of measuring the collective intelligence of groups. We will determine whether the striking pattern of correlation in individuals’ performance across a wide range of tasks even exists for human-machine groups. Then we will develop statistically validated tests for measuring the key components of collective intelligence in human-machine groups.
- Next, in order to better understand the “active ingredients” of collective intelligence, we will combine what is already known about how groups of people interact effectively with new approaches for modeling the information processing that occurs in human-machine groups. A key goal will be to find critical factors (such as group size, communication patterns, or individual capabilities) that determine a human-machine group’s performance across a wide range of tasks.
- Finally, we will use the results of these first two approaches to develop and test computational tools or other methods for increasing the collective intelligence of groups. For instance, we may develop and test new tools for filtering information more efficiently or for combining the judgments of multiple people more effectively.
*Harvard University Department of Psychology
Handbook of Collective Intelligence
This Handbook provides a survey of the field of collective intelligence, summarizing what is known, providing references to sources for further information, and suggesting possibilities for future research.
The handbook is structured as a wiki, a collection of on-line pages, editable by their readers.
The handbook is hosted by the MIT Center for Collective Intelligence, but we hope that researchers and others from around the world will contribute to it. The process of creating this handbook could itself be an example of collective intelligence.
The Centibots 100 Robot Project
The Centibots system was a multi-robotic system developed in part by SRI. Its team of 100 small robots were built from off-the-shelf components. This video describes the distributed robot control software and subsequent demonstration.
Crowd Dynamics
Crowd Dynamics is a specialist consultancy uniquely positioned to support clients who need the safe and efficient movement of people in built and complex environments
Our experience covers pedestrian flow and the movement of people on all transport modes. We are expert in developing movement strategies for large areas, city centres, terminals etc and in deploying streetspace to make optimum use of space for both people and vehicles
Success of the business evolves from our ability to understand client needs having vast experience of mathematical tools to apply the appropriate level of science and analysis to develop and evaluate options. Critical to our success is our ability to distil and disseminate our findings in a comprehensive manner to the wide range of interrelated disciplines and parties involved in stadia, terminal, streetscape or area wide designs
The company is advising on some of the worlds most complex and prestigious projects and contributed to crowd movement strategies and management plans for many high profile events.
In addition to providing independent consultancy we support government level educational and training programmes in the understanding and application of Crowd Dynamics and supply a range of modelling tools.
Algorithmicdesign.net
This body of work is computational craft that creates consistency and precision within formal explorations. There is a conscious redefining of material constrains through pattern and code, which incubates a search for progressive manufacturing methods. Pure algorithmic design encapsulates the potential for new patterns, which manifest around generative procedures through scripted logic. This abstract material logic embodiment enables an engagement with the complexities of organizational space. Drawn from the purgatory of design, these examples demonstrate a state in computation.
Particle Swarm Optimization – James Kennedy, Russell Eberhart
A concept for the optimization of nonlinear functions using particle swarm methodology is introduced. The evolution of several paradigms is outlined, and an implementation of one of the paradigms is discussed. Benchmark testing of the paradigm is described, and applications, including nonlinear function optimization and neural network training, are proposed. The relationships between particle swarm optimization and both artificial life and genetic algorithms are described.
Particle swarm optimization is an extremely simple algorithm that seems to be effective for optimizing a wide range of functions. We view it as a mid-level form of A-life or biologically derived algorithm, occupying the space in nature between evolutionary search, which requires eons, and neural processing, which occurs on the order of milliseconds. Social optimization occurs in the time frame of ordinary experience – in fact, it is ordinary experience. In addition to its ties with A-life, particle swarm optimization has obvious ties with evolutionary computation. Conceptually, it seems to lie somewhere between genetic algorithms and evolutionary programming.
Swarm Intelligence Reading
From KokkugiaWiki
Allen, Stan. “From Object to Field,” Architecture After Geometry, ed. Peter Davidson and Donald Bates, AD, 1997 Ball, Philip. The Self-Made Tapestry: Pattern formation in nature. Oxford University Press, 2001. Bonabeau, Eric. Dorigo, Marco. Theraulaz, Guy. Swarm Intelligence: From Natural to Artificial Systems (1999). Bonabeau, Camazine, Deneubourg, Franks, Sneyd, Theraulaz. Self-Organization in Biological Systems. USA: Princeton University Press, 2001. Keller, Ed. + Leitao, Carla. Agent Intellects: Pattern as a Form of Thought, AD_Collective Intelligence, 2006, Wiley Snooks, Roland. Observations on the Emergence of Character, 306090 Vol. 11 Models, Princeton Architectural Press, New York, 2007
Algoritmos Basados en Colonias de Hormigas
Swarm Intelligence Conference 2010 >> Link
An Introduction to Ant Algorithms and Swarm Intelligence, tutorial by Marco Dorigo, at the European Conference on Artificial Intelligence (ECAI 2002), Lyon, France, July 22, 2002.
Algoritmos Basados en Colonias de Hormigas, plenary talk by Thomas Stützle, at the First Spanish Congress on Evolutionary and Bio-inspired Algorithms (AEB’02), Merida, Spain. February, 2002.
Swarm Matter – Kokkugia / Pablo Kohan
Swarm Matter is an ongoing project exploring the generation of ornamental geometries through agent based formation of non-linear hierarchies and emergent patterns. The research project questions the contemporary understanding of component logic as elements which are subservient to a topological ordering device such as surface. Instead this exploration looks at the ability of the macro order to emerge from the interaction of components at a local level. Consequently instead of arraying components on surfaces these components are distributed using an algorithmic swarm logic and parametrically adjust based on their neighbors. This agent or collective intelligence embedded within the components avoids the need for an a priori distinction between various tectonic elements and enables a dissolution of normative architectonic hierarchies. This is an investigation into creating a constantly shifting relationship between line, component and surface. While there are no hierarchies encoded into the Swarm Matter project, local and shifting hierarchies arise as an emergent property of the system. The project is concerned both with the emergence of figure through complex order from a field as well as the dissolution of the figure into abstraction. At a local level a component has no base state, but will adapt to its condition, consequently while local moments of periodicity may occur a definitive reading of the component is resisted by its constant shifting to another state based on its swarm relationship. Similarly symmetries while not being inherent within the system, emerge from specific interactions of components.
Evolutionary swarm design of architectural idea models
http://www.vonmammen.org/science/t01pap320-vonmammen.pdf
| Sebastian von Mammen | ||
| Christian Jacob | University of Calgary, Calgary, AB, Canada |
Visual Representation of Swarm Algorithms / by Reza Ali
INTERVIEW WITH ROLAND SNOOKS
You are using swarm/network intelligence as a process of creation. Would you say that it is a form of loss of control from the architect ? If it is the case why would you think it is relevant in our era ?
Designing through complex systems, in particular through multi-agent design methodologies, does not represent a loss of control in the design process, however the nature of design and authorship changes. It is a shift from invention of form to the orchestration of processes. Within highly volatile algorithmic design processes topology and dimension are not directly controlled, however the formal and organisational characteristics, which are tied to the internal behavior of the algorithm are controlled through an iterative design process.
Swarm intelligence is based on a neighborhood negotiation; how do you make that happen as a designer ?
Swarm Intelligence involves the encoding of design intent at the local level through seeding agents with behaviors. It is the interaction of these behaviors that generates a collective intelligence and complex order. Consequently it shifts not only the operation of the design process, but also the design intent to the micro scale.
What are the political impacts of such a process ?
Agent based systems do not have any a priori political bias, however the distributed nature of the process offers the opportunity to use this design methodology in a more inclusive or democratic way. The interaction of a diverse set of individual desires are capable of self-organising into a coherent whole without homogenizing its constitutate parts.
Would you say that we are heading towards an interactive ubiquity ? May you tell us a short story about it ?It is not the interactive aspect of swarm algorithms that are the focus of Kokkugia’s projects or academic research. We are less interested in applying these algorithms for their real-time interactive possibility or for the simulation of reality. Instead we are intrigued by the possibilities these techniques offer for generating new situations and emergent order.
2010 QuantumBIM – Kas Oosterhuis & Hyperbody Research Group
QUANTUM ARCHITECTURE – John Lobell
In the period of classic modernism, from the 1920s through the 1940s, there was an intense awareness of the impact of relativistic space-time on architecture as evidenced in Gideon’s Space Time and Architecture . We today are in the midst of an equally revolutionary upheaval in our awareness of space and time, yet we have not systematically rethought this most fundamental aspect of architecture. This essay is meant to serve as a brief outline of some of the issues we will have to address in our new quantum world of entanglement, superposition, M-branes, parallel universes, strings, and quantum computing. The world, even on an everyday level, is a lot stranger than we think it is.
Hyperbodies – Kas Oosterhuis
E-motieve wall:
The FinRay structure is a prototype for an emotive wall. The emotive FinRay wall is composed of seven separate wall pieces, which can swing their body back and forth. Embedded in the skin of the FinRay are arrays of LED luminaries, which can be programmed individually to give personalized information or just to create an ambient luminescent atmosphere. While the primary synchronous behavior of the firefly is flashing light, the primary synchronous behavior of the FinRay is movement. In the installation, the FinRays are aligned in a row in 7 wall pieces, herein referred to as nodes. The synchronous behavior between the FinRay nodes contrasts with the motion produced by the presence of the participant. The result is a series of complex wave patterns that propagate through the FinRay structure as a whole. The propagating movements of the FinRay are expressed in the changing patterns of light and sound. The LED skins respond directly to user presence by glowing brighter when users are near, and glowing dimmer as they move away. The synchronous and asynchronous behaviors are reflected in the sound design as changes in intensity in response to the FinRay movement. Moments of synchronous behavior are represented by calmer sounds, while asynchronous behavior results more intense sound.
Swarm Intelligence: An Interview with Eric Bonabeau – O’Reilly Media
Swarm Intelligence: An Interview with Eric Bonabeau – O’Reilly Media.
by Derrick Story
Multi-Swarm Problem Solving Networks
by Tony White
Evolutionary Swarm Design of Architectural Idea Models
In this paper we present a swarm grammar system that
makes use of bio-inspired mechanisms of reproduction, com-
munication and construction in order to build three-dimensional
structures. Ultimately, the created structures serve
as idea models that lend themselves to inspirations for ar-
chitectural designs.
Appealing design requires structural complexity. In order
to computationally evolve swarm grammar con gurations
that yield interesting architectural models, we observe
their productivity, coordination, eciency, and their unfolding
diversity during the simulations. In particular, we measure
the numbers of collaborators in each swarm individual’s
neighborhood, and we count the types of expressed swarm
agents and built construction elements. At the end of the
simulation the computation time is saved and the created
structures are rated with respect to their approximation of
pre-de ned shapes. These ratings are incorporated into the
tness function of a genetic algorithm. We show that the
conducted measurements are useful to direct an evolutionary
search towards interesting yet well-constrained architectural
idea models.
Swarm Dynamics – Pablo Miranda Carranza
Swarm Behaviour – Jonas Sin
‘Fibrous structure’ inherits the properties of fluidity and flexibility to generate multi-directional circulations manifested in a hyperlinked system. Fibrous Structures aimed to explore the potential for design innovationusing parametric modeling tools and fiber-reinforced super-fluid concretes, which is developed from line- to surface technique, which line could mesh together into surfaces to create a porous system (‘nets’) where holesare co-evolve with the geometry.The most important conceptual gesture is the one ofconvergence, the design has distinguishable programme, but as a whole it does not have discretely differentparts. This means that the design is not a result of a composition of different parts, but it is but one gesture,one fluid circulatory system, incorporating different programs. The fibers techniques are translated into varied dimensions to become one formal structural and architectural system, ranging from extra large scale (mega structure of thebuilding) to extra small scale (handle of a balustrade).
HYPERBODIES: Complex Adaptive Dynamic Multi-Agent Systems (CADMAS) as Self-Sufficient Sustainable Environments of Inhabitance (SS SEI)
ABSTRACT:
Considering the question of sustainability and not only focusing in bio-climatic matters, a way of approaching this problem would be generating Complex Dynamic Adaptive Multi-Agent Systems (CADMAS) as environments of inhabitance. Not only because of the properties and characteristics mentioned in the paper of adaptive systems; able to shift and automatically adapt to their environmental conditions as represented in the work of Kas Oosterhuis. but also as a potential to grow by auto-re-generating processes. The much referenced term of ‘hyperbody’ used typically to describe a situation between the digital and the real, we feel is perhaps better suited to a concept of self sufficient sustainability, based on the CADMAS principal. This is the basis of sustainability in terms of self-sufficiency defined as ‘auto-poiesis’ (Maruyama 1963). The paper develops principals of this ‘hyperbody’ and through discussion of Complex Adaptive, Emergent, Auto-Reproductive and Auto-Organizational Systems, suggests principals for how a new kind of sustainable architecture might be derived.
Human Interaction – IAAC
The complexity in our cities is the human interaction, this can be related with the interaction of thousands of different species in the nature. Swarm architecture feeds on data derived from social transactions. Swarm architecture is a true transarchitecture since it builds new transaction spaces, which are at the same time emotive, transactive, interactive and collaborative.
When we look at an urban environment from the point of view of Swarm Architecture we no longer see isolated objects, instead we see objects which have a relation with each other. Swarm-based urban planning is an intriguing and very dynamic design game. It is really challenging for the designer to find the rules that generate excitement in the cities.
http://www.red3d.com/cwr/
http://www.swarmintelligence.org/
http://en.wikipedia.org/wiki/Swarm_intelligence
http://www.sce.carleton.ca/netmanage/tony/swarm.html
http://www.terraswarm.com/traffic_primer/bpp/index.html
http://www.vergenet.net/~conrad/boids/
http://interactivearchitectures.blogspot.com/2007/07/emergent-forms-self-organizing.html
http://www.tudelft.nl/live/pagina.jsp?id=407c2973-51f6-4d55-8c7f-99e60e1f818a&lang=en
Boids – Craig Reynolds
In 1986 I made a computer model of coordinated animal motion such as bird flocks and fish schools. It was based on three dimensional computational geometry of the sort normally used in computer animation or computer aided design. I called the generic simulated flocking creatures boids. The basic flocking model consists of three simple steering behaviors which describe how an individual boid maneuvers based on the positions and velocities its nearby flockmates
Swarm Architecture II – TUDelft
Space is a computation
…Instead of focusing on the material appearance of spaces which are built after imagining the movements of people, we must pay more attention to the membranes of those spaces in the design process and to the openings in the membranes allowing for the flow of information in whatever form…
Emergent Forms – self organizing structures
“..based on my postulation that every member of an architectural construct is, in essence, based on a computed behavior of discrete quanta. These quanta can represent anything from the smalles building component to the largest building blocks of a metropolis, anything from one single perosn to multinational institutions, as long as they behave in real time, and as long as their behavior can be computed real time.”
GameSetandMatch II: the architecture co-laboratory – TUDelft
GameSetandMatch II charts current achievements in the application of contemporary technologies and techniques to the architectural practice and explores the culturally endowing output of these technological alterations, focusing on open source sharing, bi-directional networks, swarm behavior, intelligent agents, and complex adaptive systems in general.
Fundamentals of Multiagent Systems – José M Vidal
Multiagent Systems – Artificial Intelligence (AI) Magazine
Katia P. Sycara
AI Magazine
American Association for Artificial Intelligence
Agent-based systems technology has generated lots of excitement in recent years because of its promise as a new paradigm for conceptualizing, designing, and implementing software systems. This promise is particularly attractive for creating software that operates in environments that are distributed and open, such as the internet. Currently, the great majority of agent-based systems consist of a single agent. However, as the technology matures and addresses increasingly complex applications, the need for systems that consist of multiple agents that communicate in a peer-topeer fashion is becoming apparent. Central to the design and effective operation of such multiagent systems (MASs) are a core set of issues and research questions that have been studied over the years by the distributed AI community. In this article, I present some of the critical notions in MASs and the research work that has addressed them. I organize these notions around the concept of problem-solving coherence, which I believe is one of the most critical overall characteristics that an MAS should exhibit.
The Genius of Swarms – National Geographic
A colony can solve problems unthinkable for individual ants, such as finding the shortest path to the best food source, allocating workers to different tasks, or defending a territory from neighbors. As individuals, ants might be tiny dummies, but as colonies they respond quickly and effectively to their environment. They do it with something called swarm intelligence.
SWARM ARCHITECTURE 