..Introduction
..Understanding the city as a system
..Cities optimize information exchange
..Different types of complexity
..Systems and modular decomposition
..Plug and play' strategies are misleading

Introduction

Cities coordinate activities requiring complex patterns of cooperation among a large number of human beings. Furthermore, this must be accomplished under conditions in which the activities are changing continuously. Jane Jacobs (1961) contrasts static cities such as 19th century Manchester with dynamic cities such as Birmingham (England). Manchester was very successful in the cotton industry, but declined in the face of external competition. It has never been possible to point to one industry by which Birmingham earns its living; rather its capability has been the creation of new industries in response to changed conditions. Other roles with which successful cities are associated include assignment of resources and maintaining order across expanding empires (16th and 17th century Madrid; 18th and 19th century London) and providing exchange and port services under dynamic trade conditions (medieval Venice).
Coordinating a complex combination of changing functions drives other natural and artificial systems such as biological brains and real-time electronic systems. In the case of electronic systems, functional change occurs under explicit intellectual control. That is, the desired functional change is decided beforehand and then specified in complete detail. This requires extensive testing before its implementation in order to avoid undesirable side effects. For cities and biological brains, on the other hand, change is to a considerable degree heuristic (i.e. learned by the system itself in response to experience).
The need to change functionality forces a complex system to be modular at many levels (Coward, 2000). Following the example of electronic systems, "modules" are defined as clumps of activity that have larger information exchange within the module than with other modules (Courtois, 1985; Parnas et al, 1985). In a city, a functional module at the most detailed level could identify a person with the buildings and spaces in which most of his or her time is spent. At a somewhat higher level, modules could include small groups of people who interact strongly on a daily basis with various urban nodes. At a yet higher level, modules correspond approximately with institutions, individual businesses, educational and political organizations, etc. The correspondence is only approximate, because a major city function at the highest level may be partly in a specialist module, but some elements of it may reside within other modules.
It is important to point out that our use of the term "module" is more akin to "network" than to a geometrically compact object or region. This paper is liable to be misunderstood if the reader incorrectly envisions a functional module as some physical built cube, to be moved around much as a LEGO block on a board. Our modules enclose distributed patterns of interactivity. They are more dendritic in structure, and thus any attempt to understand them must first overcome the twentieth-century urban model of non-interacting entities placed rigidly on a rectangular grid.
A system needs to minimize the overall cost of information exchange. Analysis of a city as a system should therefore begin by identifying groups of people who exchange more information within the group than external to that group. Groups on any level cannot be identified cognitively in advance, but only on the basis of differential information exchange. Intervention would then try to enhance city functionality by making information exchange more efficient. City modules in general do not correspond with simple city functions. Urban structure needs to be assessed by abandoning strict visual ordering based on aerial geometry, and concentrating instead on the evolving information and movement networks.
Information exchange at a detailed level includes conversation, observation, or display by individuals (Meier, 1962). At a higher level it is people or groups of people moving from one function to another. The networks of a city, the paths, roads, telecommunications, etc. are the mechanisms that support information exchange. A complex pattern of information exchange coordinates city functions, drives a city's dynamics, and determines its evolving structure. Also, the need to change heuristically results in all such information exchange being partially ambiguous. By this we mean that it recommends but cannot demand specific actions.

Understanding the city as a system

An earlier paper (Salingaros, 1998) formulates urban functions in terms of relationships and movement. Nodes of human activity such as home, work, park, store, restaurant, church, etc. are connected into a network. One way of understanding their success is that people moving along such paths for the purpose of higher level information exchange can carry out lower level information exchange with other modules (e.g. observing). The time required for higher level exchange is therefore used more effectively. A subsequent paper (Salingaros, 1999) confirms one instance of this. The use of urban space is linked to the information field generated by surrounding surfaces, and to how easily the information can be received by pedestrians. This information is functional; it can recommend secondary behaviors to the observer who is executing a primary information exchange.
Information and communications technologies need to be incorporated into traditional city functions (Drewe, 1999; 2000). The dynamics of the rapidly evolving electronic city are as yet little understood, while the twentieth-century model of a city based on simplistic geometrical ordering is irrelevant for modeling a communications network. Blocks of functionally segregated buildings, strictly aligned to a rectangular grid, do not reveal the various overlapping networks that actually drive a city to function (Dupuy, 1991; 1995). As a complex system whose output is commercial wealth and culture, a city has a functional architecture based on information exchange (Meier, 1962). Information and communications technologies should fit neatly into the hierarchy of information exchange functions at different levels of scale.
Our work is part of recent attempts to understand cities as complex systems, including those by Peter Allen (1997), Juval Portugali (2000), and their collaborators. Christopher Alexander pioneered the understanding of complex city structure, studying urban form in more realistic ways than the simplistic geometry of the CIAM model (Salingaros, 2001). He and his colleagues have published seminal statements about how a city grows and repairs itself (Alexander, 1965; 2003; Alexander et al, 1975; 1987). Most important have been the pointed comparisons between the processes whereby a living city develops, and a pathological city decays. That body of work includes specific guidelines on how to build a living city; what legislation is needed to do so; the distribution of money in urban projects; the specific urban design process to follow; etc. Practicing urbanists will need to implement practical strategies to heal decaying cities, and generate new, living cities.
Information architecture implies that city form is dynamic, and it evolves heuristically. This conclusion questions much of current planning practice. What is required instead is a process of diagnosis and repair of the urban fabric, much as biological tissue calls upon mechanisms to repair itself. Such a process of urban design is precisely what Alexander and his colleagues have been insisting upon all along. Clearly, the fact that those proposals represent the opposite of the post-war CIAM approach to planning has discouraged their implementation up until now. Our original aim in writing this paper was unrelated to Alexander; we wanted to understand a living city's system architecture in an abstract, theoretical manner. Perhaps our conclusions will now give a needed boost to work we believe to be both correct and prescient.

Cities optimize information exchange

Optimization means that a maximum of information is exchanged with a minimum of effort. In a city, many people need to change location in order to coordinate two functions. An information activity could be made more efficient by generating other information exchanges than just the primary one (e.g. via observation during a move from one location to another). Walking to an appointment in a European capital can be more pleasant than a drive to achieve the same end in a North American metropolitan area. One sees other people, some of whom one might wish to talk to; observing others may provide clues on social currents and interactions; window displays provide information on available products and services. Of course, we are discounting negative factors which interfere with effective information exchange such as crime, inclement weather, overcrowding, etc.
The cost of information exchange in most urban activities is woefully underestimated. A half hour trip has a cost and a value. How much valuable information exchange occurs? Do you see a wide range of behaviors? Are you exposed to people you want to influence? Would a city be more effective if people saw more directly what was going on? Note the tradeoff with television -- while "walking around" you are doing the selection, but may get lots of irrelevant information; with television, you can focus the relevance of the information but someone else is doing the selection. Shopping malls minimize information exchange costs for one cognitively defined function (shopping) but result in excessive information exchange requirements for many other functions such as transportation.
Naively separating shopping areas from office areas and housing areas creates serious problems. First, any information exchange between these functions will be high cost. Second, there is little scope for components with necessary functions but no physical structure/location to contain them (in contrast to, say, a restaurant). Informational networks do not possess a compact geometry, hence do not fit neatly into a geometrical module. They are and will always be at odds with a city that is restricted to a simplistic visual plan. And yet, informational networks are what make up a living city. It is certainly impractical to design the informational networks of a major city in advance, and in any case, as the functions of the city evolve, it is vital that the city have the capability to evolve heuristically. No leadership will be able to anticipate and manage this at all levels of detail (Salingaros, 2001).
Consider, for example, the process by which decisions are made to invest in a new business. Such decisions require coordination between future technology directions, market needs, financial resources, and business resources. This knowledge will be distributed across many city modules. A city with efficient information exchange of the required type will be more effective in creating new business than one without. However, creation of new business is not the only city function requiring a complex pattern of information exchange, and so there is a conflict between the information exchange needs of different functions. Ideally, the result will be a compromise that allows all functions to operate effectively. There must also exist mechanisms for adjusting this compromise as functional needs change.
The functional role of an intermediate level module such as a restaurant includes preparing meals from raw food; distributing prepared food for take-out; maybe offering candy and souvenirs for sale; educating people on how to dress or behave; hosting meetings between people to discuss business or politics; etc. This module is contained within the building which houses the restaurant. Some restaurants become focal points for information exchange in a city -- often identified with a particular business in a large metropolitan area, or the restaurant is an important node in a small town's social and government networks. The larger module then includes the restaurant as a submodule, and reaches out to include spatial patterns of activity in the neighborhood. The parking arrangements, footpaths, and proximity to other locations all affect the ease and effectiveness of information exchange within this larger module.
Nodes that do not form part of a larger module are often parasitic to the city, since they use its infrastructure without contributing to an overall functional coherence. Nevertheless, that is how restaurants, stores, supermarkets, and office buildings are built nowadays. Entirely surrounded by a parking lot, they are designed as if they are going to be built in the middle of the wilderness, yet they are forced right into the urban fabric, tearing it in the process. Restaurants designed to work as highway truck stops are routinely erected inside the city, but they don't belong to it. People working in a nearby office building, which could provide clientele at lunchtime, frequently have to drive their cars along a busy road to get to a restaurant that is literally next door.
Planners have adopted urban typologies that are essentially anti-urban, and which are destroying our cities. Designs are approved that are irrelevant to the local urban fabric -- every building ignores its context and tries to be independent of ANY context. It satisfies the insensitive corporate approach of "one size fits all" based on cost-cutting, and the desire (driven by greed) to connect this node to the entire city without bothering to give preferential treatment to the local urban fabric. Not only are local connections not given any consideration; they are explicitly excluded, making it impossible to connect to neighboring buildings. It is naively expected that a new building will connect instantly to the entire city, while totally ignoring the prohibitive costs of doing so. This approach, however, merely reflects the destructive modernist philosophy -- no concession to the surroundings, which means no connectivity.
Information exchange in a residential area occurs through learning how neighbors manage their environment. Discussions with neighbors and meetings for local planning create an informational network, which is the social "glue" holding a neighborhood together. Just as the electricity, water, and road networks define connectivity for the region in a functional sense (Dupuy, 1991), so the informational network defines a neighborhood rather than a cluster of isolated buildings. Suburbia consists of isolated house nodes, and is thus devoid of the older information exchange network among neighbors (Salingaros, 1998). There is simply no social cohesion -- a true neighborhood is ruled out by suburban geometry. The only thing left is the appearance of one's house as a display to influence others; an event that assumes particular meaning during holidays such as Christmas when people decorate their houses' exteriors. The size of a house's façade makes a statement about the owner's income level and social aspirations.
Environmental information is an important part of maintaining order. Litter in the street implies that more serious crimes are tolerated there, whereas clean subways give the message that someone is watching. Peer pressure and public demonstrations help establish social order. Observing how others behave is very important, and getting what you want in a particular situation depends partially on how you behave. The loss of social cohesion in a region -- and on a larger level, the loss of community in urban society -- starts by eliminating information exchange between neighboring residences. Planners pushed house fronts too far back for effective personal communication between neighbors. Other physical components of interpersonal neighborhood information exchange like the front porch and the wide, walkable sidewalk were suppressed. We forgot that for millennia, the hustle and bustle of urban street life generated commercial interactions that created wealth for nations.

Different types of complexity

A wide range of systems are called complex, and it is important to recognize major differences between distinct types of complexity. We identify two broad categories of complexity -- FUNCTIONAL, and PHYSICAL. Cities are functionally complex, and analogies based on physical complexity (like chaos theory) can be misleading. Thinking of a city as merely physically complex mistakenly leads some authors to think that cleaning up physical complexity will solve urban problems. In fact, since that idea is based on a serious misunderstanding of system architecture, it almost inevitably leads to disaster.
In a physically complex system there is in general a small number of component types, and all components of one type are identical. The interaction between two components depends primarily on the types of the components and the distance between them. Complexity in this case derives from the very large number of connections of the same type among many similar components. On the other hand, while in a functionally complex system there could still be a small number of component types, different components of the same type are similar but not identical. The interaction between any pair of components is in general unique to that particular pair. We thus have a very large number of connections, but each one is identifiable and distinct.
The two different types of complexity imply drastically different system properties and behaviors. In a physically complex system, very slightly different starting states can give rise to radically different end points. This so-called called "chaotic" behavior is a key reason for the difficulty of weather prediction. In a functionally complex system, however, slightly different starting points will tend to give rise to similar end points (i.e. similar input conditions should generate similar behaviors). Partial insensitivity to input variability guarantees stability -- called "homeostasis" in living systems, which are functionally complex. Convergence on appropriate end points is achieved by controlling the available variability at the system level.
Clearly then, a functionally complex system is characterized not by identical components and interactions, but rather by uniquely individual components interacting in distinct ways. Even before we get to the core of our discussion, we are in a strong position to identify the modernist city -- consisting of identical units interacting in the same way -- as pathological. It encapsulates the extreme industrial view of a human being as a mass-produced unit, denying any identity to the individual. Moreover, physical complexity is unavoidable for systemic reasons, despite the visual appearance of "order" imposed by the geometry. By contrast, living cities are functionally complex, while their individualistic components and interactions give the misleading appearance of physical disorder as seen on a plan.

Systems and modular decomposition

Complex systems are coherent working wholes that cannot be completely separated into fully independent modules. A structure that can easily be separated into non-interacting constituents is not a complex system, but rather an aggregation of units (called a "heap" in systems theory). Nevertheless, separation into modules with some degree of interaction is widely used both for the design of artificial systems, and for the understanding of natural systems. As pointed out earlier, modules are defined as clumps of activity which interact more strongly within the module than external to it. Herbert Simon (1962) has argued that there could be a small number of inequivalent separations of a system into components, all of which might make some sense because they identify different subsystems (Salingaros, 2001).
Any functionally complex system, whether natural or artificial, is forced into a hierarchy of functional modules for two reasons (Coward, 2000; 2001). The first reason is that there are always advantages in minimizing the volume of information (design or genetic) required to build the system. As a result, such systems tend to contain a relatively small number of fundamentally different types of components. The system will be constructed from large numbers of a few basic types, with relatively slight variations within one type.
The second reason is that any system needs to fix problems, and to make functional changes that do not disrupt existing functionality. Knowledge of a problem to be fixed, or a functional change to be made generally exists at a fairly high level (e.g. a feature does not work properly; an area of the city is declining). The necessary actions, however, must be taken on a much more detailed level (e.g. replace a specific group of transistors; implement investment and regulatory actions). One has to find and follow logical paths that link high level conditions with detailed actions. The existence of such connections linking the higher with the lower system levels requires a modular hierarchy. This means that the highest level functionality of the system is separated into modules, these modules into submodules, and so on through a series of levels down to the primary components.
All modules on one level must be roughly equal in terms of the number of primary component operations each module contains. External information exchange among modules that is needed to coordinate module functionality must be minimized as far as possible. If one module were much larger than the others, then most logical paths would pass through that one module, which would result in centralization instead of the distribution of functions.
Very large information exchange between two modules precludes their effective separation for the purpose of tracing logical paths. The requirement that modules be separated so that information exchange be minimized corresponds with Courtois' (1985) point that the join between modules will be successful if it occurs along a region that is weaker than any module's internal connections. The geographical separation of residences from workplaces through monofunctional zoning is a case in point. Because these two regions interact so strongly, they do NOT define separate functional modules, despite the simplistic expectations of planners. Instead, the geometry forces functional module formation of the most inconvenient kind, with information exchange that is very expensive to maintain.
Designing extremely complex electronic systems begins with a more-or-less arbitrary separation of functionality into roughly equal size modules, followed by performing functional scenarios to determine information exchange. If this exchange is excessive across modules, functionality in the form of subunits is shifted between modules (i.e. the partition into modules is redefined) until a compromise is reached between module equality and minimized information exchange. The point is that no preconception, such as neat geometrical ordering, can ever determine the partition into functional modules (Salingaros, 2001). Defining modules by this process of finding compromise means that such modules may have a very complex geometry. Also, the relationship with high level system features is going to be nontrivial, with one module contributing to many overlapping features. This process is then repeated with the modules at the next smaller level of detail, and so on.

Plug and play' strategies are misleading

Reusability of modules is a central concept in design, but it gives planners a false understanding of systems. "Plug and play" strategies in modular design offer the possibility of replacing a module that fails, or which is superseded by an improved module. This also allows a module to be added to a system without rearranging the entire system. Conversely, a module can be removed when not needed, without requiring a complete reorganization. Plug-in complex modules became popular during World War II in military hardware. Savings in time resulting from the ability to quickly service a complex mechanism -- usually with no specialized training -- overrode the higher cost of replacing a module instead of fixing one of the module's internal components. The same mentality has been inherited by the computer industry, with throwaway modules as today's hardware standard. All of this depends on an interface that permits modules to connect easily to the system.
This plug and play capability is quite misleading, however, because it has been achieved by functionally simplifying hardware, and moving most of the functional complexity into software. It is extremely difficult to achieve "plug and play" with software modules in a complex real time system, unless the functions performed by different modules have very little interaction (Garlan et al, 1995).
The idea of replaceable hardware modules established an entirely negative precedent for planners. Electronic or mechanical modules tend to be complex subunits. Any savings in replacing the entire module comes not from hardware costs, but in the short down time for the entire system. One pays to replace a very expensive physical module instead of fixing one of its faulty cheap components in a situation where any repair time must be kept to a minimum. This makes sense in a bomber or aircraft carrier, for example, but is meaningless in a city. An urban system is more like an organism, requiring a lengthy and careful diagnosis followed by minimal intervention rather than an organ transplant.
Planners picked up the idea of a physical module as a result of thinking about physical complexity, and missed the fact that cities form functional modules. This has led to the major typological and planning errors of today. A new residential subdivision or an office tower is approved, with the expectation that these physical modules will neatly plug into the existing city. Today's cities grow in precisely this fashion. As soon as one of these physical modules is plugged in, however, urban forces create functional modules that do not look like anything envisioned by planners. Those functional modules are usually forced to be sub-optimal by the infrastructure and zoning, which are geared to support the integrity of the (urbanistically irrelevant) physical modules. The inability of today's cities to form functional modules leads to urban pathologies.
If we had to find a city analogy for the hardware/software separation in computers, the obvious choice would be to identify hardware with buildings, spaces, and infrastructure; whereas software would correspond with people exchanging information through communication and movement. We know that early twentieth century urbanists adopted mass-production techniques from manufacturing, and applied them to cities. One of these was the extreme simplification of city hardware, in the misguided attempt to implement the idea of reusable modules. One should not be surprised, therefore, at the system consequences of this action -- physical separation and segregation of functions leads to overburdening people's daily movement with all the functional complexity removed from the city's built structure. The simplistic visual ordering of modernist planning, therefore, has as its unintended consequence an extreme functional complication (hence overloading) of the transportation network.
The need of a city to recover from problems and modify functionality is shared by natural systems such as biological brains. Such systems are also forced to adopt a hierarchy of modules, with the appropriate compromise between module equality and the need to minimize information exchange among modules. Absence of such a system architecture will in the case of brains result in a brain which has difficulty in recovering from physical damage, or in learning without disrupting earlier learning. A species with such a brain is likely to become extinct. In the case of a city, absence of such an architecture will reveal itself in the inability of finding solutions to urban problems, or responding to changing conditions.
Segregating urban functions (the paradigm for modernist planning universally adopted after World War II) creates aggregates of high level separations that maximizes the cost of information exchange (Salingaros, 1998; 2001). This is the opposite of functional modularization. The need for communication at many other levels in addition to within the selected urban aggregates creates excessive information exchange at an expensive level (e.g. traffic jams), inefficient information exchange (e.g. unproductive time wasted in commuter journeys), the inability of the city as a whole to adjust to changing conditions (e.g. urban decline), or most likely all three.

The nature of functional modules in a city

Suppose that city functionality at the highest level were experimentally defined in terms of modules (that is, someone takes a best guess on what elements might be grouped together to form individual modules). Even trying to define any single module brings out the key issue. High level functions are in fact physically and institutionally distributed across any living city. To act in a coordinated and effective manner, individuals and groups of people are required to interact in a pattern which will not neatly correspond with the defined functions. In general, it will not be possible for functional modules to be given neat cognitive labels.
A geographical area such as an office park demonstrates this. Typically, there will be much less interaction between different offices in the park than between each individual office and its headquarters, branch locations, customers, suppliers, bankers, etc. Such an area is therefore not a functional module, which invalidates the "office park" as a useful urban typology, despite its recent proliferation. For similar reasons a region of suburban houses is not a functional module (Salingaros, 2001). Creating office parks and suburban house regions makes all genuine functional exchange high cost (or imposes systemic isolation). This is the system force behind Jane Jacobs' (1961) observation that successful city neighborhoods are always mixed usage.
If information exchange within a city module occurs mainly via direct personal interaction between people, then physical proximity is necessary. This will minimize the travel required. On every level, modules associated with physical areas will perform activities which require the exchange of information, but will relate in a very complex fashion to city functions. Only the most simplistic functions (i.e. those requiring minimal interaction with any other functions) can be physically separated without loss of city effectiveness. The information exchange needs of different modules will compete, and thus it may be physically impossible to satisfy all the modules' needs for physical proximity to other modules. A compromise definition of modules which minimizes overall information exchange is therefore inevitable.
Consider now some of the obstacles that may be encountered in establishing effective information exchange. If a business or other group discovers the need for intensive personal interaction with groups of people in a different area of the city, the solution is to move next to each other (Hallowell, 1999). If no suitable premises are available (e.g. because of the real estate situation, or planning restrictions) then module functionality will suffer. In a different scenario, if there is a need for informal information exchange in a casual environment between a number of groups already within an area, but there is no location (e.g. a coffee house) available, again module functionality will suffer.
Creating physical modules naively by separating identifiable city functions will in general result in an inefficient pattern of information exchange. That, in turn, leads to city dysfunctionality. How can/does a city achieve an effective modular structure and the corresponding networks to support the required information exchange? Given the complexity of real cities, no individual or group of individuals will have the intellectual capacity or the necessary information to identify the detailed changes needed to improve city effectiveness. Even in an electronic system made up of transistors rather than people, it is extremely difficult to identify the changes needed to implement a desired change without undesirable side effects. Typically, provisional changes are identified, and extensive testing of all system functionality is performed to verify that the new function works as desired, and no undesirable side effects occur. This type of testing is not an option for a city, however.
The solution is for a city to define its own modules and networks in a distributed fashion. In other words, partitioning into modules has to evolve, with existing modules on every level contributing to functional changes. This change management may in fact be the most complex function performed by a city. It requires that a city adopt some of the forms of the recommendation architecture visible in human brains, to address issues such as context for information exchange between modules, and resolution of conflicting behavioral recommendations from different modules. The effectiveness of different cities can then be compared in terms of the relative effectiveness of their module hierarchies. We are devoting the remainder of this paper to explain these issues in detail.

A city works like a brain, not a computer

Different system architectures characterize complex systems that work in a different manner, as for example a digital computer versus a mammalian brain. The functionality of an electronic system is expressed as a series of commands in software. The use of unambiguous contexts results in the familiar memory/processing separation of the von Neumann system architecture upon which most computers are based (Coward, 2000). Information exchanged between two modules must have an unambiguous meaning to the recipient module in terms of its own functionality. Modules can then use their input information to generate outputs that are commands for the system.
Maintaining unambiguous contexts is impractical in a complex system such as a city, however, which has to heuristically modify its own functionality, or learn. In a system that learns, modules must heuristically determine their own inputs and outputs (i.e. learn by trial and error). Nevertheless, if a module changes its outputs, it is difficult for modules which have previously received inputs from that module to readjust. The receiving modules cannot assign an unambiguous meaning to the new output. Therefore, outputs from modules can only change gradually, in ways that minimize the loss of meaning to other modules. In a city, this means that healthy urban fabric is generated by a slow evolution, and also a city must be allowed to evolve over time. On the other hand, radical redevelopment of healthy urban fabric destroys meaningful information exchanged within the city. The result is city dysfunction until enough time has passed to rebuild information contexts.
There are thus two possible information architectures for a complex system. One is the von Neumann architecture with a memory/processing separation supporting unambiguous information exchange, in which functionality is explicitly controlled. The other is the recommendation architecture with a clustering/competition separation supporting meaningful yet slightly ambiguous information exchange, in which functionality is defined heuristically (Coward, 2000; 2001). A competition subsystem interprets the outputs of submodules as a range of alternative behaviors, and quickly selects one of the alternatives. This process depends critically on consequence feedback to determine appropriate system behavior.
When it is necessary for functionality to change heuristically, or without central direction, a system adopts the recommendation architecture. Biological brains have evolved a recommendation architecture (Coward, 1990; 2000; 2001). In the mammalian brain the clustering/competition separation corresponds with the anatomical separation between cortex and subcortical structures (Coward, 2000). Commercial electronic systems, on the other hand, invariably use the von Neumann architecture. In the most complex electronic systems it is extremely difficult to evolve functionality in a controlled fashion. When a change is made, extensive testing and error correction is required, with the testing covering not just the modified functionality, but examples of all different system functions.
Since the recommendation architecture uses more resources that the von Neumann architecture to perform the same functionality, if there is no need for functional change, operational forces push the system towards the von Neumann architecture. Information exchange then tends to become unambiguous because the action required in every condition is well understood. However, if conditions begin to change, such a system will find it very hard to adapt. The system can no longer find an effective compromise between module equality and information exchange, which reveals itself in a steadily decreasing ability to make changes. The failure of 19th century Manchester is one example. The city became extremely efficient for the cotton industry, but could not adapt when circumstances changed.
Resolution of conflicting recommendations must occur in an institutionally separate function which does not require complex coordination. Electoral and legal institutions perform this role. There are interesting similarities between the competitive subsystem as defined here, and legal and political mechanisms. In a physiological brain the competitive function will in general choose one or another option rather than try to find a compromise, because it is impossible to know whether a compromise will not make things worse. Thus the legal and government regulation process for resolving conflict in general selects a winner from amongst existing alternatives rather than generating novel behavior.

Ambiguous information recommends actions

An effective pedestrian space is one which provides useful information that helps to determine our behavior and movement (Salingaros, 1999). It should answer questions like -- how should I behave in this area; what can I learn in this area; who can I meet in this area; what can I do in this area; which way do I go to get to the function I am looking for? The provided information is not a command, but a set of choices that has to be integrated with other recommendations and the needs of the observer to generate a behavior. Functional information cannot be replaced by geometrical information. In courtyards and amphitheaters, for example, it is not so much the geometry as the human meaning which is attached to the geometry that determines their effectiveness as spatial structures.
How another person behaves in a particular location is information that constitutes a recommendation. A walk in a city area provides observations that are partially ambiguous from the point of view of how to behave there. Information exchange also includes conversations and personal visits. In some cases exchanging information may lead to a physical transaction such as the purchase of a product. Different information is communicated by sending the head of an organization than by sending someone at working level. Either way, the information exchange is partially ambiguous because a range of different subsequent behaviors of the two functions may be consistent with the information exchanged during the visit.
Learning the meaning of visual information is a major attraction for visits to European cities which have only changed gradually over hundreds of years. Undirected wandering in such cities allows the visitor to accept recommendations offered by different visual environments and to discover the results of such acceptance. It is thus possible to learn the "visual language" of the unfamiliar city. For example, one may learn how to find places by observing and following trends in the visual environment. This is true to a much lesser degree in North American cities, where everything tends to be explicit (for example, the visual markers of chain stores and restaurants). In many cases, rapid redevelopment has destroyed the context for visual information over wide areas.
It is interesting to consider first the suppression, then the spontaneous reappearance of competing environmental information. Modernist planners decreed that human beings had to move from point A to point B in their daily lives, so no recommendation from different available choices was ever needed. The post-war built environment reflected this philosophy -- everything was highly deterministic. In the 1950's, however, the human brain's recommendation architecture had begun to reassert itself in the visual choices offered by advertising. Messages competing for attention created the visual chaos of billboards in the North American commercial strip. The problem is that partially ambiguous information is extremely dangerous to the driver of a car, yet it is precisely what enriches a pedestrian journey.

The role of telecommunications

As has been well documented (Droege, 1997; Graham and Marvin, 1996), the advent of telecommunications ever since the introduction of the telephone dramatically altered urban systems. Information exchange intensified to a degree that was previously unimaginable. Telecommunications is low cost in the sense that it requires very little physical movement of people. One of the principal reasons for the initial aggregation of people into cities was in order to communicate with each other at low cost, and this is still the driving force behind, say, the Diamond districts of New York City and Antwerp. It could be argued that the need for persons in the same trade to cluster is in part replaced by telecommunications. However, this is only true if the type of information exchanged by telecommunications is exactly the same as that exchanged by personal contact.
Some authors predicted that telecommunications would replace commuting. The reasons this prediction failed are not hard to see when analyzed from the information architecture perspective. Information exchanged through personal contact and people movement has a much richer content, including information derived from a combination of voice tone, expression, and body language (Hallowell, 1999). In addition, a visit allows the visitor to observe the quality of office, style of working, and coworker relationships of the visited person, and allows the visited person to observe the reaction of the visitor to these conditions. The multiplicity of sources of environmental information cannot be duplicated by a restricted number of communications channels.
Large corporations have generally found that introducing new communications mechanisms such as e-mail or videoconferencing does not in fact reduce the amount of physical travel. The effect of the new communication capability is to increase the complexity of projects which can then be undertaken, rather than to replace existing communications. The exception is that if a new communication mechanism results in the same information exchange at lower cost in resources or time, the new one will replace the old. Examples are the replacement of telegraph by fax, and the replacement in North America of interstate train travel by air travel.
Telecommunications fits into the hierarchy of different channels of movement and information exchange in a city (Drewe, 1999; 2000). Working from home via an electronic link is now feasible, and there are several instances of successful applications. First, a mother with small children at home, and a handicapped or elderly individual can now link to informational nodes that would otherwise be too costly (in terms of time and arrangements) to interact with physically. Second, powerful and wealthy individuals set up residence in some fancy resort, and conduct their business via electronic links. This is made possible because their financial resources enable them to have all necessary information available, and any personal level of information exchange is taken care of by a quick trip. The module here is an informationally stimulating environment for those who can afford it.
An office worker can in principle work from home to perform a task that requires only a narrow information link. Someone stuck in an informationally starved environment may not be altogether happy to work exclusively from home, however. He or she normally prefers to fight rush-hour traffic because that at least gives some informational stimulation, and enables face-to-face information exchange with coworkers. Suburbanites spend hours on the telephone and in front of the television for this very reason, and still feel informationally deprived. The workplace has for many people replaced the home as the primary social node. People don't want just to eliminate the ordeal of a lengthy daily commute by car, bus, or train; they want to get their daily information exchange at a lesser cost. Today we pay an inordinately high price in automobile traffic for very little meaningful information.

Networks and evolving city form

Unless adequate meaning can be conveyed by telecommunications, information exchange will involve the movement of people. An effective transportation network will allow a high proportion of required information exchange to take place via short walks (say < 10 minutes each way) with secondary information exchange; an intermediate proportion to take place by moderate overhead mechanical transport (say < 30 minutes each way); and only a small proportion requiring high overhead mechanical transport (say from 30 minutes to 1 hour each way). Journeys which occupy in total much of a working day will in general be ruled out. The distribution of both pathlengths and journey times should follow an inverse-power scaling law favoring the small scale -- the number of paths is inversely proportional to their length (Salingaros, 2001).
Creating an effective network depends on the functional partitioning of the city, and will always require a compromise. The decision to reduce the overhead for one type of trip may increase the overhead for another type of trip. For example, widening a road and increasing vehicular traffic may make many pedestrian trips across the new road much longer, or make them altogether impractical, thus destroying a working functional module. It is therefore essential to investigate whether an apparent demand for a new high level network connection such as a major road could be addressed by a different module partitioning, which might reduce the need for trips in the direction of the proposed road.
An example of this process in action can be found in Jane Jacobs (1961). A city planner (Robert Moses) wanted to widen a road through a neighborhood at the expense of neighborhood sidewalks. The reduction in sidewalks was resisted by the neighborhood, which managed to gain enough political support through alliances with other neighborhoods to not only prevent the sidewalk reduction, but in fact to get sidewalk widening. It turned out that the traffic on the affected road was reduced (presumably it was carrying longer range traffic rather than local pedestrian traffic), but there was no sign of increased traffic on other roads in the area. The implication is that many of the car journeys on the target road were replaced by shorter (presumably somewhat less effective) journeys. The result is that overall city effectiveness improved.
A city's connectivity at different levels down to capillarity is responsible for its life. Dead zones are a result of loss of network connectivity. Spatial nodes and their network are interdependent, and their mutual causality reveals the dynamic evolution of city form. Networks follow the functional reorganization of a city as it tries to make itself more connected on all levels. Automobiles and pedestrians connect at the pedestrian system level, but the car works entirely on a distinct, higher system level. Gabriel Dupuy has initiated a clearer understanding of these problems (Dupuy, 1995; 1999). The systems approach clears away decades of misunderstandings that led to such acts of violence to urban systems as cutting expressways through historical city cores. The automobile network must adapt itself into -- rather than disrupt or replace -- the network of information exchange that powers a compact, living city.
Change in a city is ubiquitous. The goal of urbanism is to help a city evolve and redefine its modules so they can modify their functionality. It is not easy to determine the appropriate module and network changes so as to respond to changes in the city's needs and environment. Urban change must be a natural built-in function of the system, driven by a complex pattern of information exchange. As discussed earlier, centrally directed changes typically introduce large numbers of unanticipated and undesirable side effects. Any attempt at total central direction of modules and networks on every level will result in steadily increasing dysfunctionality. In spite of this, planning now focuses on large-scale interventions, and does not tolerate spontaneous evolution driven by input at different levels.
Different modules on every level will need to generate alternative recommendations for module and network change. A simple competitive process must select the most appropriate change. Consequence feedback then has to adjust the competitive subsystem to evolve its selections towards those that optimize the network. Knowledge relevant to one change may exist on a number of levels. There must therefore be mechanisms by which modules at many different levels of detail recommend change, which can then be received, interpreted, and integrated into a decision that optimizes overall city effectiveness. Less successful cities can copy explicitly from more successful cities, provided that the functional relationships are copied, and not just physical structures and individual institutions.

Conclusion

We identified the system architecture of cities by comparing them to complex information systems such as computers, biological organisms, and the human brain. A city works according to an information architecture that recommends, but does not demand an action. Functionality on all levels of scale is driven by the need to optimize information exchange, from a face-to-face meeting between two persons, to the movement of individuals, up to the daily movement of many people between urban nodes. Functional modules should develop in a way such that more information is exchanged within a module than between different modules. Cities, like human brains but unlike electronic systems, must modify their functionality without explicit intellectual control over every detail of the change. Our model allows us to help a living city repair itself much as a living organism does, and to guide its evolution under changing conditions. Rather than using models based on visually regular aerial geometries, this approach makes it possible to evaluate changes to city plans, zoning codes, transportation, and communication networks in terms of their impact on overall city effectiveness.

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