Posts Tagged ‘Complexity’

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New paper: Knowledge Problem

February 9, 2012

Lynne Kiesling

I have a new paper that may be of interest to KP readers, since the subject of the paper is the same as the name of this site: Knowledge Problem. I am honored to have been invited to contribute this paper to the forthcoming Oxford Encyclopedia of Austrian Economics (Peter Boettke and Chris Coyne, eds.). Here’s the abstract:

Hayek’s (1945) elaboration of the difficulty of aggregating diffuse private knowledge is the best-known articulation of the knowledge problem, and is an example of the difficulty of coordinating individual plans and choices in the ubiquitous and unavoidable presence of dispersed, private, subjective knowledge; prices communicate some of this private knowledge and thus serve as knowledge surrogates. The knowledge problem has a deep provenance in economics and epistemology. Subsequent scholars have also developed the knowledge problem in various directions, and have applied it to areas such as robust political economy. In fact, the knowledge problem is a deep epistemological challenge, one with which several scholars in the Austrian tradition have grappled. This essay analyzes the development of the knowledge problem in its two main categories: the complexity knowledge problem (coordination in the face of diffuse private knowledge) and the contextual knowledge problem (some knowledge relevant to such coordination does not exist outside of the market context). It also provides an overview of the development of the knowledge problem as a concept that has both complexity and epistemic dimensions, the knowledge problemʼs relation to and differences from modern game theory and mechanism design, and its implications for institutional design and robust political economy.

In this paper I analyze the development of the two categories of the knowledge problem — the complexity knowledge problem and the contextual knowledge problem — and explore both the history of the development of these concepts and their application in robust political economy and new institutional economics. As is the hallmark of a good research project, I think on balance I learned more than I created in the process of writing this paper.

One other thing I made sure to include was a discussion of how the knowledge problem and its development relates to game theory and mechanism design, through the work of Oskar Morgenstern (and then through some of the work of Herb Simon and Vernon Smith, among others).

Tying together economics, institutional design, history of thought, and epistemology, I hope you find this paper informative and useful! I’ll also make sure to update when the full volume is available.


Posted in Complexity, Economics | Tagged , , , , | 3 Comments »

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Music, harmony, and social cooperation

December 23, 2011

Lynne Kiesling

I am a big fan of English renaissance choral music, particularly sacred polyphony from Tallis and Byrd (and stretching back to Taverner, but he’s not as distinctively polyphonic). One of the best ensembles performing such music is Stile Antico, a group of 13 British singers who do an outstanding job with this music, and whose recordings I have recommended here before. Especially at this time of year, their music really resonates and adds joy and beauty to life.

A couple of weeks ago we got to hear Stile Antico perform live in Milwaukee: Thomas Tallis’ Puer Natus Est mass interspersed with pieces from Byrd, White, and Taverner. The music was gorgeous, the voices delightful, and the artists charming and gracious.

But what really struck me was their method of decentralized coordination. Typically when we think of musical performance beyond, say, a chamber quintet, coordination involves hierarchy in the form of a conductor, to “keep everyone on the same page”. The larger the number of performers doing different things, the harder to coordinate, and therefore the greater need for a conductor … right?

Not so in this case. 13 singers, each with a particular part, bringing a distinctive element to the work. But in some ways the music is simultaneously so lush and yet so spare that if their timing is off, the beauty of the result is diminished. 13 singers with no conductor, and they coordinate by taking their visual and verbal cues from each other in a dynamic and evolutionary manner. This is a vivid example of decentralized coordination.

Of course the goal is harmony (in the general sense). If each individual acts and reacts to the actions of the other individuals in a way that produces a harmonious outcome, that’s beauty. And it’s an emergent outcome; each has his or her own score and acts accordingly, adapting to the actions of the others in a way that creates emergent harmony.

The music metaphor illustrates achieving emergent order through decentralized coordination, and it’s a metaphor for social cooperation too. Adam Smith employs the harmony metaphor for social cooperation in The Theory of Moral Sentiments, in which he invokes harmony as a desirable outcome of social interaction repeatedly (and refers to the music metaphor directly in the last reference). Note the emphasis on harmony as distinct from uniformity — each individual brings personal, private, heterogeneous features to social interaction (whether musical or economic), and they are not the same, not uniform. Each has an incentive, a desire to coordinate, to harmonize; in music it’s finding the complementary notes, in social systems it’s grounded in our innate desire for sympathy and mutual sympathy, according to Smith. Each individual brings something different to the party/performance/market.  The most beautiful and sublime outcomes emerge when each acts on its individual traits with a view toward creating harmony and sympathy. And it does not necessarily require the top-down imposition of control or system-wide hierarchy, but can be achieved through decentralized coordination.

Of course there are limits to applying the music metaphor to institutional design and social cooperation, such as the scale/number of actors. But it reminds us of the possibility of cooperation and harmony through decentralized coordination, without the need for imposed system-level control.

 

Posted in Complexity, Economics | Tagged , , , | 7 Comments »

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Students for Liberty talk: economics and complexity

October 3, 2011

Lynne Kiesling

UPDATE: I’ve had a report that the link to the slides is not working, but I can’t get it not to work … so if you are having trouble please let me know in the comments and I’ll go bug-stomping. UPDATED UPDATE: mischief managed, I think!

On Saturday I was honored to be the morning keynote speaker at the Students for Liberty Chicago Regional Conference. In only four years SFL has grown into a large and effective organization for bringing together students who share an interest in exploring and promoting individual liberty, classical liberal ideas, and public policy that reflects those principles.

My talk, Beneficial Complexity (pdf of slides), took some basic economic concepts and looked at them through the lens of complexity science. My main objective was to encourage the attendees to see ways to integrate some core classical liberal ideas into their own thinking, their own work, their persuasive discussions with others, and their advocacy activities.

Start with a story: a flower market selling calla lilies grown in Colombia. Lots of buyers and sellers, lots of parties involved in getting the flowers from places like Colombia to your neighborhood flower shop. Mostly impersonal exchange, but not entirely devoid of personal relationships. And without any one person knowing how to do so in its entirety, the flowers get from Colombia to my flower shop for me to buy. If you are familiar with Leonard Reed’s I, Pencil essay about the highly decentralized yet coordinated processes that combine to bring pencils to consumers, you recognize this theme. One of the fundamental economic and epistemological concepts that I, Pencil illustrates is the knowledge problem — no one person knows how to make a pencil, or how to grow and sell calla lilies globally. We associate this idea primarily with the work of F.A. Hayek, as stated in his famous essay “The Use of Knowledge in Society” in 1945 (which also inspires the title of this blog).

Knowledge is dispersed and, importantly, it is also private and often subjective. Your willingness to use some of your resources to buy a cup of coffee, or a pencil or a calla lily bouquet, is known only to you and is context dependent, which means that much of the knowledge that goes into individual decisions is local and hard to centralize. Yet calla lilies show up in Chicago shops, as do pencils, in ways that satisfy the preferences of consumers and profit producers along the supply chain. How does that happen? Markets and prices create networks of dispersed, local, private knowledge that connects and aggregates that knowledge and sends valuable signals to economic actors about the relative benefits and costs of the decisions they take.

When we think about economic activity taking place in networks, and how exchange and prices connect networks and extend and deepen them, we are using the tools of complexity science to understand economic behavior. Think back to the flower market and the pencil. As Eric Beinhocker writes in The Origin of Wealth, “The complexity of all this activity is mind-boggling. … all the jobs that must get done, all the things that need to get coordinated, and the timing and sequence of everything. … there is no one in charge of the global to-do list. … Yet, extraordinarily, these sorts of things happen every day in a bottom-up, self-organized way. … The economy is a marvel of complexity.” (2006, pp. 5-6)

Technically speaking, what is a complex system? It’s a system or arrangement of many component parts, and those parts interact. These interactions generate outcomes that you could not necessarily have predicted in advance. In other words, it’s a non-deterministic system. Scholars in many different fields use this general idea to study a range of systems and phenomena, from molecular and cellular interactions in physics, chemistry, or biology, to the organization of the brain in neuroscience, to species and environment interactions in ecosystems, to cascading network failures in electric power systems, to networks of co-author collaborations in particular fields of research, and many other applications.

These applications share an interest in three features of a complex system: its structure (how are the parts connected, how do they interact?), its rules (physical or human-generated), and its behavior. apply this idea of a complex system to our economic and social interactions. Go back to Beinhocker’s description of the market economy as “a marvel of complexity” in which all sorts of activities get coordinated in a “bottom-up, self-organized way”. Think of the economy as a complex system, in which individuals are the agents, the component parts, with dispersed private knowledge. We are connected in many ways — social relations, economic exchange, organizations, and so on — and our interactions shape individual decisions, individual behavior, and ultimately overall system behavior. The profound insights of writers like Ferguson, Smith, Hayek, and others is that individual agents have their own preferences and private knowledge, but we interact, and in so doing we generate system-level behavior that is generally self-organized — emergent order. In this unplanned order no one person can predict the specific outcome we’ll achieve, but we still experience over and over and over in human history that order generally does emerge.

But order doesn’t necessarily always emerge, and the order that emerges sometimes isn’t pretty. That observation leads to the elephant in the room with respect to emergent order in social system: the rules. All exchange takes place within a framework of rules, an institutional context. Those institutions include formal laws enforcing property ownership, contracts, and punishment for theft and fraud, as well as informal social norms and peer pressure that may, for example, affect how the bargaining and negotiation in the exchange take place. Rules shape how agents interact, and shape their incentives … and as a result they can also affect system behavior. One important implication of studying economies as complex systems is that when we design institutions, we should model and test and strive for rules that enable order to emerge, which means an emphasis on process rather than using rules to achieve some specific outcome. That’s one important intersection of classical liberal principles with complexity science.

I’d like to raise a point that I didn’t in my remarks on Saturday, but builds on a discussion in a later session at the conference. One challenge that we often face as classical liberals is putting “the human face” on our ideas, countering the perception that a libertarian society would be cold, calculating, and lacking in compassion or personal relationships. Nothing is further from the truth, and the language of complexity science gives us a way to communicate that reality, because it frames economic/social interactions as relationships and connections. It emphasizes the mutuality of exchange and the multiple dimensions of our relationships with others in our voluntary associations.

Posted in Complexity, Economics, Liberty | Tagged , , , | 2 Comments »

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Resiliency comes from more risk of bank failure, not less

September 21, 2011

Lynne Kiesling

In the always-smart-and-interesting City AM paper from London, Anthony Evans makes an important argument that has been overlooked in financial regulation debates: risk of failure is what creates system resilience, and regulation creates brittle monocultures. He writes in the context of last week’s Independent Commission on Banking (ICB) recommendations for creating regulatory divisions between retail banking and investment banking and implementing other structural changes, with the objective of a more resilient financial system. Evans critiques the over-simplified concept of risk that the report employs:

We can’t say that one thing is more risky than another – only that different activities expose people to different types of risk. Bodies like the ICB needs to shift from trying to – impossibly – reduce risk to placing responsibility on those who are choosing between different risks.

For example, ordinary depositors should not be protected from risk – they need to confront it. It can seem counterintuitive, but the genuine threat of bank runs is probably the best disciplinary device to prevent them from happening.

Evans’ argument stems from an assertion that he makes later in his column, that risk cannot be reduced but can only be transferred from one party to another. While I think that assertion is debatable, the important insight from this part of his argument is that resiliency in complex market systems arises from agents having responsibility for losses associated with taking additional risks, in addition to their receiving profits associated with taking additional risks. Breaking that connection among risk, profit, and loss is one of the core causes of the brittleness of the financial system over the past two decades, and the transmission and magnification of those losses.

Evans makes a second important observation: when regulation imposes a higher degree of uniformity in a complex system, it reduces resilience of the overall system by creating separated monocultures:

By making arbitrary decisions about what must stay within fences and what doesn’t, or about the level of equity capital that banks will be required to keep, regulators make banking more homogenous. Banks are already free to set up their own ring fences, and a competitive system would be one where they can experiment with different ones. …

All regulations create clusters of errors – by their nature they harmonise behaviour and therefore increase systemic dangers. Policy efforts need to focus on reducing barriers to exit, making it easier for banks to fail, making the costs of failure more visible and ensuring they fall on those who make bad decisions – bankers, regulators, or even the public.

We see this paradox of control in all forms of economic regulation; in this case in financial regulation, but also in the electricity regulation that is the focus of my attention. Regulators believe that by increasing control, by limiting the range of actions that agents can take in complex systems, they are reducing the risk of bad outcomes. But what they do not realize (or choose to ignore) is, as Evans points out here, that by imposing more top-down centralized control on their actions and interactions, they reduce the incentives of the agents to develop their own forms of individual control based on their local knowledge and their own experimentation. Thus regulation makes this complex system more rigid, more brittle, less resilient, and therefore regulation does not achieve its stated goals.

Note here that I am using the tools and language of complexity science and complexity economics, but you can see in this discussion where moral hazard shows up, where you could talk about the failures of corporate governance (as does Charlie Calomiris), etc. Framing the objective as a resilient system broadens the focus beyond top-down regulation to include the individual, decentralized institutions that can keep dangers from becoming systemic. Thinking about regulation in terms of the locus of control and the consequences of the imposition of control in a complex system is more likely to enable us to incorporate the costs of imposing control into the analysis, and to harness decentralized institutions to enable a more resilient system.

Posted in Complexity, Economics | Tagged , , , | 1 Comment »

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David Warsh on complexity and economics

June 28, 2010

Lynne Kiesling

David Warsh’s Economic Principals column this week is about complexity, and the study of complexity in economics. It is as informative and insightful as Warsh’s columns usually are, despite its selective coverage. He highlights some ideas that I think are important for the future direction of economics — the isolation of the twin methodological peaks of what David Colander calls the “summit of Mt. Walras” and Warsh calls “Game Theory Massif”, a brief history of complexity economics since the 1980s, and the extent to which complexity necessitates a change in research methodology to incorporate work like agent-based modeling and variables that are less “formalizable” on Mt. Walras, such as institutions and knowledge.

This was not Warsh’s purpose in his column, but I’d expand beyond his column to incorporate the intersection of his ideas with Hayek’s “Theory of Complex Phenomena” (1967) and the general relevance of the knowledge problem to why and how phenomena are complex. In social systems, diffuse private knowledge is a big reason why complex social systems evolve, and why we discover and design rules that exploit that complexity to get better outcomes. Markets and prices are just the most obvious and pervasive example, but there are multitudes of others.

I recommend Warsh’s column, both today and as a worthwhile weekly read, for some good thought provocation and for some discussion of the ideas that animate the work here at Knowledge Problem and related ideas.

Posted in Complexity, Economics | Tagged , | 2 Comments »

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Some complexity-based thoughts on macro

October 26, 2009

Lynne Kiesling

I am doing a lot of reading and thinking, trying to make some headway on a way-overdue paper, and have been reading a striking working paper from David Colander, Richard Holt, and Barkley Rosser, “The Complexity Era in Economics” (August 2009). Their insights are directed toward the evolution of economics methodology and the absorption of complexity-related concepts and techniques. In addition to being relevant to my own work on regulatory institutions and technological change, I found the paper insightful in the context of the discussion a couple of weeks ago about this year’s new institutional economics Nobel prize and the dominant methodological hegemony in economics.

One of their interesting observations is also pertinent to the reexamination of macroeconomic theory in light of the financial market context of the past year and a half. This quote, in particular, illustrates what I find especially striking in macroeconomics:

However, while the new theoretical models have done a good job in eliminating the old theory, it is less clear as to what the new theoretical work has added to our understanding of the macro economy. At best, the results of the new macro models can be roughly calibrated with the empirical evidence, but often the calibration of these new models is no better than any other model, and the only claim they have to being preferred is aesthetic—they have micro foundations. However, it is a strange micro foundation—a micro foundation based on assumptions of no heterogeneous agent interaction, when, for many people intuitively, it is precisely the heterogeneous agent interaction that leads to central characteristics of the macro economy.

It’s also interesting that in that section they footnote Leijonhufvud, who wrote the only macroeconomic theory that I ever felt like I had any kind of grasp on, On Keynesian Economics and the Economics of Keynes:A Study in Monetary Theory.

If you haven’t had you fill of current critiques of macro theory, and you are interested in reading their thoughts on the evolution of economics to incorporate the analysis of economic systems as complex adaptive systems, I recommend this short working paper.

Posted in Complexity, Economics | Tagged , , | Comments Off

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Emergent orders are all around us, especially in cities

September 10, 2009

Lynne Kiesling

Ron Bailey’s Hit & Run post, Ant Hills=Brains=Cities, reminded me of some really important, fundamental ideas that tend to get lost as we natter about financial regulation, health care regulation, climate regulation …

Emergent orders abound, and occur at all sorts of different scales — molecular, cellular, all the way to complex social structures that were not deliberately designed through some central planning group or function. Ron cites the excellent Godel, Escher, Bach to introduce some new research arguing that cities are like brains in their emergent order construction for successful functioning. Ron quotes Mark Changizi, a neurobiology expert and assistant professor in the Department of Cognitive Science at Rensselaer Polytechnic Institute:

… brains and cities, as they grow larger, have to be similarly densely interconnected to function optimally.

Interesting. Not surprising, especially if you’ve thought about emergent orders, and double-especially if you’ve read any of Jane Jacobs’ writing on cities. I recommend the Jacobs interview at Reason that Ron links, as well as other Jacobs sources linked in the various posts I’ve written invoking Jane Jacobs and her work over the past several years.

Given how much attention we are having to pay to imposed orders, and the increasing efforts to create more deeply imposed orders in finance, healthcare, etc., it’s important to remember how much of the social life of individuals is a web of emergent orders, and that the biggest and best value creation and thriving and innovation that we have seen in human history arises when individuals can choose and take action in emergent orders.

Posted in Complexity, Economics | Tagged , , , | 2 Comments »

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Resilience, sustainability, and loosely-coupled systems

May 4, 2009

Lynne Kiesling

The NIST smart grid interoperability roadmap workshop I attended last week has gotten me thinking about the similarities between system architecture (as the computer systems folks call it) and institutional design (as we political economy social scientists call it). Of course there’s quite a bit of similarity, as the work of the GridWise Architecture Council (to which I’ve been honored to contribute) demonstrates. And I’ve always argued for institutional design that allows for adaptation to unknown and changing conditions, applying institutions to what I think of as an evolutionary test.

One of the concepts that fall logically out of this way of thinking about systems and institutions is resilience. This article from the forthcoming issue of Foreign Policy (thanks to Jesse Walker at Reason) focuses on resilience, in the context of thinking about the financial crisis of the past year:

Resilience, conversely, accepts that change is inevitable and in many cases out of our hands, focusing instead on the need to be able to withstand the unexpected.

The author contrasts this dynamic, adaptation-focused concept with sustainability, which he views as a more static, maintain-the-status-quo approach. I’m not sure I agree with that; I think it’s possible to have a dynamic concept of sustainability … but then it becomes resilient sustainability. Or at least that’s what I teach my MBA students, that true sustainability is in fact resilience.

One crucial aspect of resilience in a complex “system of systems”, whether it’s a network of computer systems or a network of individual economic agents interacting in a network of markets (or the intersection of the two!), is the extent to which the different parts of the systems are “coupled”. That’s what I’ve been mulling over for the past week — loosely-coupled systems. Loose coupling is a term of art in computer systems. Interestingly, its Wikipedia entry caught my eye for the precise reason I wanted to incorporate it into this post:

Loose coupling describes a resilient relationship between two or more systems or organizations with some kind of exchange relationship. Each end of the transaction makes its requirements explicit and makes few assumptions about the other end.

This definition highlights the aspects that are important, especially from a smart grid architecture perspective and an institutional design perspective: different systems or organizations with some kind of exchange relationship. Loose coupling means that entities that are engaged in exchange have to understand and exchange certain kinds of information to make those exchanges happen, but these requirements are explicit, and they are not exhaustive. When I buy milk at the grocery store, I don’t have to know the name of the cow whose milk I’m buying … but I do want to know some product features, such as its fat content, the sterility of its production environment (here, admittedly, aided by safety regulations), as well as its price. If my transaction relies on that specific cow, that’s a more tightly-coupled relationship, and if she dies and the transaction relies on it being her milk, then the transaction fails. A simple-minded example, but you get the idea.

Loose coupling is like having shock absorbers at the interfaces between different entities and different systems in a complex “system of systems”. Loose coupling can help prevent the negative consequences of unexpected actions from propagating through the network, and that’s how it contributes to resilience.

The electric power network today is very tightly coupled, both physically and economically, which reduces its resilience in the face of unknown and changing conditions. One of the most important arguments in favor of smart grid investments is that digital smart grid technology enables looser physical coupling and looser economic coupling, to the mutual benefit of both producers and consumers. At an architectural and institutional design level, that means developing architectural principles (including interoperability principles and standards) and legal and regulatory institutions that enable individual economic agents in the electric power network to create long-lasting, resilient value in these loosely-coupled systems.

I’m going to continue thinking about how these ideas relate; at this point I’m just thinking out loud, so please chime in to help me refine my ideas.

Posted in Economics, Electricity | Tagged , , | 12 Comments »

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Peer-to-peer power through microgrids

April 21, 2009

Lynne Kiesling

When we think of concepts like peer-to-peer networks and disintermediation, we usually think of industries that are very Internet-centric. But these concepts can, should, and will apply in electric power networks too: smart grid technology enables peer-to-peer power.

The study referenced in that BBC article analyzes the potential for microgrids, and argues that the real potential from applying smart grid technology to create microgrids is in the ability to create a neighborhood peer-to-peer network in which neighboring customers can buy and sell from each other:

“A microgrid is a collection of small generators for a collection of users in close proximity,” explained Dr Markvart, whose research appears in the Royal Academy of Engineering’s Ingenia magazine.

“It supplies heat through the household, but you already have cables in the ground, so it is easy to construct an electricity network. Then you create some sort of control network.”

That network could be made into a smart grid using more sophisticated software and grid computing technologies.

As an analogy, the microgrids could work like peer-to-peer file-sharing technologies, such as BitTorrents, where demand is split up and shared around the network of “users”.

As distributed generation and plug-in hybrid vehicles proliferate in the market, more numbers and types of electricity consumers will have the resources to be both buyers and sellers in such a peer-to-peer network. Look, for example, at the picture of a P2P network at the Wikipedia peer-to-peer entry.

Now imagine that instead of computers, each of the entities depicted on this network is a home or small business in a microgrid network. Power, and commercial transactions, can flow in both directions between pairs on the network, and they can flow between any pairs of agents who have agreed to participate. Just think of what that can do to reliability, especially if you pair it up with transactive, price-responsive end-use technologies that have the type of behavior I described in this post on smart grid and complexity and this post on how intelligent end-use devices make a transactive smart grid valuable.

If you are interested in learning more about a microgrid project, here’s a report on the Galvin Electricity Initiative prototype microgrid project at the Illinois Institute of Technology. It focuses on the technical details and capabilities of a microgrid to provide reliable, high-quality electric power service, not on the microgrid’s transactive capabilities, but it’s a good introduction.

The technology exists for P2P power networks. The institutional structure, though, does not allow for such a decentralized, transactive network — the regulatory environment typically does not allow microgrids for a variety of reasons, including the monopoly granted to the local utility on the construction of distribution wires that cross public rights-of-way.

Posted in Complexity, Economics, Electricity | Tagged , , | 1 Comment »

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Smart grid, complexity, and swarm logic

April 15, 2009

Lynne Kiesling

One of the recurring themes here at KP is that smart grid technology makes it possible to harness distributed intelligence in the electric power network, and when you couple that network of distributed intelligence with a decentralized flow of information (such as price signals and market processes), you can get reliability through decentralized coordination instead of through the imposition of hierarchical control. Moreover, because individual agents are voluntarily coordinating instead of being forced into a control structure, it’s likely that decentralized coordination generates more social surplus, increases total welfare, etc.

Here’s an exciting new building intelligence product than can start to deliver on that vision. As described in this CNet article, Regen Energy is producing wireless device controllers that, when networked, can adjust device energy use based on individualized, decentralized trigger settings:

Rather than send specific instructions to each controller, the system sets parameters, such as cutting power consumption at peak times during the day. The EnviroGrid controllers individually make adjustments to the chillers, such as turning them off for 10 minutes out of an hour, which in aggregate hit the overall goal, Kerbel explained.

“We tell the controllers, ‘Here are some rough guidelines for upper and lower limits’ (of energy consumption) and they do the work,” he said. “Right now, the way to do this sort of thing is to get a building engineer who does an analysis and then get a software programmer to write custom code.”

The technology is a prime example of how computer and networking technologies are quickly being applied to the energy industry to improve efficiency.

The decentralized decision-making approach is also a break with tradition central building management systems where building equipment is typically purchased for peak power demands.

Yes, indeed it is! It’s also a break with the top-down control hierarchy mindset that pervades the engineering, the regulatory, and the business model cultures in this industry.

Regen refers to their technology as using “swarm logic”, based on the complex adaptive systems ideas of self-organization and emergent order as seen in bees, ants, and other large populations that coordinate with the use of distributed intelligence, rules for responding to observed behavior, and limited hierarchy. As I argue in my book, based on the work of Hayek and other complexity-oriented economists, this kind of self-organization and emergent order also characterizes healthy, competitive markets.

A recent Technology Review article also gives a nice overview of the technology and the idea of swarm logic:

“Every node thinks for itself,” says Mark Kerbel, cofounder and chief executive officer of REGEN Energy, which invented the proprietary algorithm embedded in each device. Before making a decision, he explains, a node will consider the circumstances of other nodes in its network. For example, if a refrigerator needs to cycle on to maintain a minimum temperature, a node connected to a fan or pump will stay off for an extra 15 minutes to keep power use below a certain threshold. “The devices must satisfy the local restraint but simultaneously satisfy the system objective,” says Kerbel, adding that a typical building might have between 10 and 40 controllers working together in a single “hive.” The devices are simple and quick to install and, because there’s no human intervention, require no special training to use.

It’s a dramatic departure from the top-down command model associated with current building-automation systems. Some researchers say that the decentralized approach to energy management offers a cheaper, more effective way to manage supply and demand in a delicately balanced electricity system. Indeed, some believe that it could be an early prescription for an emerging smart grid.

In this case the only hierarchy imposed from the system controller is some global objective function, such as minimizing overall energy use. Each device controller is programmed with trigger points, such as total system use or frequency level, and is then also programmed to take an action once it is at the trigger; note that this trigger is also likely to be more granular and smaller-scale than, say, a “turn off” command, so the functionality of the device to the consumer will only be minimally affected. In aggregate, the individual actions of the distributed responsive devices achieve the system objective without impairing functionality or consumer value in any meaningful way. And using this swarm logic and self-organization model to harness distributed intelligence is also saving consumers money:

Tests have so far demonstrated that building owners–of hospitals, hotels, shopping malls, factories, and other large facilities–could save as much as 30 percent on their peak-demand charges. Those savings, REGEN claims, more than cover the cost of renting the devices, which is an option for major electricity consumers reluctant to buy the technology up front. If the devices are purchased, the payback is less than three years, says Kerbel.

Thus far it sounds like Regen’s device controllers are responding to data on physical conditions. But it’s not a difficult stretch to enable the distributed controllers to respond to price signals, which would make them transactive. Different types of devices could have different trigger price settings, reflecting the preferences of the building owner. Once they do that, Regen would probably pass my transactive test.

Posted in Complexity, Economics, Electricity | Tagged , , , | 4 Comments »

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