Philosophy and Simulation

The Emergence of Synthetic Reason

Manuel DeLanda

• Publisher: Bloomsbury Academic
• Year: 2019
• Print ISBN:
  9781350096783
• eBook ISBN:
  9781350096776
• Edition: 1
• Topic: Philosophy
• Subtopic: Philosophy History & Theory

In this groundbreaking book, Manuel DeLanda analyzes different genres of simulation, from cellular automata and generic algorithms to neural nets and multi-agent systems, as a means to conceptualize the space of possibilities associated with casual and other capacities.

This remarkably clear philosophical discussion of a rapidly growing field, from a thinker at the forefront of research at the interface of science and the humanities, is a must-read for anyone interested in the philosophies of technology, emergence and science at all levels.

Chapter 1

THE STORM IN THE COMPUTER

Let’s begin with the simplest emergent properties, properties like temperature or pressure characterizing wholes made out of a large number of identical parts, such as a body of water in a container. Being composed of billions of molecules that are qualitatively the same makes a body of water much simpler than, say, an ecosystem in which hundreds of different species constantly interact. But this simplicity is what makes the mechanism of emergence behind temperature or pressure a promising starting point for philosophical thought. To begin with, in what sense are these properties emergent? Temperature is defined as the average energy that a molecular population has by virtue of the motion of its parts, the more violent the motion the more intense the temperature. Pressure is defined as the average degree to which the population pushes against the walls of the container by virtue of the momentum of its parts, the faster and more massive the molecules the more intense the pressure exerted. These definitions have tempted philosophers in the past to think that temperature and pressure can be reduced to kinetic energy and momentum, that is, that they are not emergent. But temperature and pressure are in fact irreducible because they are the result of an objective averaging process that takes place spontaneously in molecular populations.

To understand how this works let’s imagine two bodies of water at different temperatures. The moment we place these bodies in contact with each other energy will flow from the body with higher temperature to the one with lower temperature, the flow continuing until the temperature difference disappears. In other words, the difference in temperature will display a tendency to average itself out. Thus, saying that a body of water possess a certain temperature, and that possession of that property defines an enduring state, implies that departures from that state are constantly being counteracted by an objective tendency. For the same reason defining “sameness of temperature” can be done by placing two bodies of water into contact and verifying that no flow of energy is taking place between them. Thus, in this simple case the irreducible status of a property like temperature is established by elucidating a mechanism through which the property emerges, a mechanism involving the manifestation of tendency. Accounting for this tendency, in turn, demands switching scales and focusing on the interactions between the parts of the whole, interactions in which the parts exercise their capacities to affect and be affected. In particular, for a temperature difference to cancel itself the component molecules must exercise their capacity to collide and redistribute energy in those collisions.

We can visualize the series of events leading to the emergence of an average temperature by comparing the states of two bodies of water before and after the dissipating tendency has been manifested. At the start of the process the existence of a temperature difference means that the water molecules are distributed with a high degree of order, that is, that they are neatly sorted out into two parts, one hot and the other cold. At the end of the process the entire population is uniformly warm and this order has disappeared. A disordered state is characterized by the fact that we can make a large number of changes in the molecular distribution and leave the bulk state basically the same. In other words, a much larger number of combinations of individual kinetic energies will result in the same warm body of water than the number that will yield the state in which one container is hot and the other one is cold. This affects the probability that one or the other state will occur spontaneously. Because in this case the interactions between molecules are entirely random these odds make all the difference in the world: the state characterizing a warm body of water will have a much higher probability of occurring as a result of random collisions than the one in which they are sorted into hot and cold subpopulations. It is this difference in the odds with which the ordered and disordered states can occur that explains the tendency for one to become the other.¹

The mechanism of emergence just described for temperature is basically the same for pressure, density, and other intensive properties of molecular populations. Despite their relative simplicity these properties are important because the spontaneous flow of energy that takes place as intensive differences cancel themselves can be tapped into to fuel other processes. The whole composed by two containers of water at different temperatures, for example, has the capacity to drive another process partly because the high temperature container stores a lot of energy, much more than the low temperature one, and partly because we can extract that energy by placing the former in contact with the latter.² This capacity is relatively short lived, however, because once the intensive difference disappears the energy left behind becomes much harder to extract. But if the difference is continuously refreshed, by placing the first container on top of a fire, for instance, then the whole formed by the hot and cold molecular populations can become a component part of a larger whole, playing the role that a gasoline tank or an electric battery play in an automobile or an electronic appliance. The capacity of intensive differences to act as energy storage devices will play such a prominent role in the explanation of emergence in many other examples that it will be useful to have a more compact term for them. We will refer to them as gradients.

In addition to serve as energy sources gradients can serve to generate the moving parts of larger wholes. For example, if a gradient is intense enough and if it is prevented from dissipating it can cause a molecular population to self-organize into a circular motion pattern that will persist as long as the gradient persists. The coordinated movement of billions of molecules needed to yield such a pattern is a highly unlikely event and yet it occurs spontaneously in the ocean and the atmosphere every single day. This coherent circulatory flow, referred to as a convection cell, is produced by the gradient as the means to cancel itself even as the imposed constraints prevent it from doing so.³ The mechanism of emergence behind a convection cell can be explained using the same example of a water container: when the container is heated from below it becomes divided into a warm bottom and a cool top; as the bottom water warms up it expands and becomes less dense tending to rise, while the high density cold water on top tends to sink; these up and down movements are counteracted by the internal friction generated by the viscosity of the water, but when the temperature difference becomes intense enough this resistance is overcome and the upward and downward flows join together to form a circular pattern.⁴ Because this pattern is very stable it can literally be used as a building block to construct larger emergent entities.

What kind of entities can be built using gradients as fuel tanks and convection cells as moving parts? The most dramatic example is a thunderstorm, a typical storm containing five to eight convection cells each a few kilometers in diameter.⁵ Viewed from the outside a thunderstorm appears as a large complex cloud with a well-defined form. At the center of the storm is a massive column-like structure called the “central pillar.” This vertical structure adopts an asymmetric horizontal shape at its top called an “anvil” for its resemblance to the metal block used by blacksmiths. The central pillar often overshoots the anvil creating a dome at its top. Finally, at the bottom of the pillar there are flanking horizontal clouds lined up in the opposite direction to the anvil. This complex form is one of the emergent properties of a thunderstorm, its directly observable property. But behind its observable form there is the internal machinery of the storm. In addition to gradients and convection this machinery uses phase transitions, the transition from gas to liquid or from liquid to solid, as energy amplifiers. One of the differences between a material such as water in its gas, liquid, or solid state is the degree to which its composing molecules move around and therefore the amount of kinetic energy the material contains. In a solid the molecules are relatively confined to fixed positions so their activity is relatively calm. In liquids this confinement is relaxed: molecules still exert some restraining influence over one another but they allow a more energetic movement. In gases the molecules are even more excited since their movement is not constrained at all. A gas therefore contains more energy than a liquid or a solid. When rising vapor becomes rain some of this extra energy becomes available as a surplus that can be exported to the surrounding medium, increasing the amount of energy available to the thunderstorm. This exportable energy is referred to as “latent heat.”⁶

To understand the mechanism of emergence behind a thunderstorm we need to explain how these different components are coupled together. First of all, a difference in temperature between the surface of the ocean and that of the atmosphere must exist to get the process started. This vertical gradient causes an upward flow of air and vapor forming one leg of a convection cell. As the warm moist air moves up it becomes cooler eventually reaching the critical point at which vapor becomes liquid water. At first this phase transition produces very small liquid droplets that become suspended in the surrounding air. The concentration of these tiny droplets makes the upward air current visible as a small cauliflower-shaped cloud that becomes the base of the future thunderstorm. Although at this point the air should start turning sideways and head for the downward leg of the convection cell, the latent heat released by the phase transition increases the temperature of the air current adding buoyancy to it and propelling further up. This self-stimulating interaction is repeated several times allowing the updraft to reach great heights eventually becoming the giant cloud described above, with its central pillar, anvil, and dome. The death of a thunderstorm, in turn, is linked to processes that counteract its sustaining gradients: the higher the air reaches the colder it gets, the more saturated it becomes, and the larger the liquid drops and ice crystals that condense from it. When the weight of these drops and crystals reach a tipping point—the point at which the downward force exerted by gravity becomes stronger than that of the updraft—it begins to fall in the form of rain and hail dragging air with it, stealing energy from the updraft and eventually destroying the internal machinery of the storm.

Other features of this emergent meteorological entity are also explained by gradients. A severe thunderstorm is usually accompanied by the production of lightning, either intensely bright flashes created within the cloud or powerful bolts between the cloud and the ground. Lightning is the result of an electrical gradient, a difference in charge between the upper and lower regions of the cloud, or between the cloud and the ground, the brilliant discharge being the form created by the gradient to cancel itself. Thunderstorms are also the birth place of tornadoes, whirling masses of air made visible by the matter (vapor, dust, debris) that they suck into their intensely rapid circulation.

Tornadoes are born from the same vertical temperature gradient that causes the updraft to which a steep horizontal pressure gradient is added. The latter is caused by the fact that the updraft sucks the air from the center of the tornado greatly reducing the pressure inside of it compared to that of the outside.⁷ As an emergent whole a thunderstorm is characterized by its properties, such as the heights it reaches or the speed with which it moves; by its tendencies, like its tendency to move in a certain direction or its tendency to consume all its energy and die; and by the capacities it exercises when it interacts with other entities. From a human point of view these interactions are mostly destructive: its lightning kills people and starts brush and forest fires; the heavy rain along its downdraft can result in floods; and the tornadoes it spawns can violently flatten entire towns. These capacities can surely inspire awe and respect at the destructive potential of a thunderstorm but they should not lead to an attitude of intellectual resignation or natural piety toward it: we can explain how it is born, how it lives, and how it dies.

Let’s pause to consider the argument so far. The objective reality of emergent properties can be established by elucidating the mechanisms that produce them at a one scale and by showing that emergent entities at that scale can become the component parts of a whole at a larger scale. Mechanisms of emergence may, of course, undergo revision or elaboration, and some are better understood than others, but the possibility of improvement or change in the proposed mechanisms should not force us to take emergence at any scale as a brute fact. There are, on the other hand, aspects of the concept of emergence that this argument does not address. In particular, similar emergent effects can be produced by entirely different mechanisms suggesting that there is more to the emergent properties of a whole than the interactions between its parts. Let’s return to the case of convection cells. The self-organized rhythmic flow characterizing convection emerges in many kinds of materials. The flows of molten rock that lie underneath the surface of the earth, for example, exhibit the same coherent circular motion as the air and water above it. More importantly, the same self-organization is displayed by other rhythmic patterns that have nothing to do with the movement of matter in space. A good example comes from the world of chemistry. The gradients in this case are differences in the concentration of certain substances, that is, they are gradients of matter not of energy. The rhythms are the rates at which new compound molecules are synthesized—the chemical reaction switches spontaneously from the production of one type of molecule to the production of another following a perfect beat—not collective circular motions. Yet despite these differences a convection cell and a chemical clock, as these reactions are called, are qualitatively the same. This implies that a full explanation of these emergent entities must possess a component that is independent of any particular mechanism.

It could be argued that the similarity in rhythmic behavior is sup erficial and that it does not demand complicating the concept of explanation, but there are other shared characteristics that cannot be so easily dismissed. In particular, the periodic behavior in both cases is stable against perturbations, that is, if a convection cell or a chemical clock are disturbed by an outside shock they will tend to return to their original period and amplitude after a relatively short time. This tendency is referred to as asymptotic stability. Not all oscillating entities possess this kind of stability. A pendulum in which friction has been carefully eliminated, for example, will not react the same way: a small push will permanently change both the duration and intensity of its swing, the pendulum acting as if it “remembered” the perturbation. A convection cell or a chemical clock, on the other hand, quickly “forget” the perturbation acting as if nothing had happened.⁸ When we explained convection by the causal mechanism outlined above—a temperature gradient that creates a density gradient that, in turn, amplifies fluctuations into a circular flow—we were giving only part of the explanation because the causal chain behind the emergence of a convection cell does not account for the fact that its properties are stable against perturbations. And similarly for a chemical clock.

Adding to the explanation of emergence a mechanism-independent component will involve introducing entirely new ideas so it will be useful at this point to justify the need for the extra complexity. So far the concept of emergence has played an ontological role, showing why it is legitimate to believe in the existence of objective properties, tendencies, and capacities. But once we add the mechanism-independent component the concept of emergence leads to two important episte-mological consequences: it explains why we can use partial models to learn about reality and it provides an account for the capacity of those models to mimic the behavior of the processes they model. The first consequence derives directly from the notion of asymptotic stability. When the emergent properties of a whole are stable they can survive changes in the details of the interactions between its parts. A given degree of temperature in a body of water, for example, may result from a number of different interactions between the kinetic energy of its component molecules. This implies that we can take the existence of temperature for granted when explaining the circulatory pattern in a convection cell, that is, that we can legitimately leave out of the explanation a detailed census of the kinetic energy of each of the molecules in the population. To put this differently, a stable emergent property is “indifferent” to local changes in the interactions that give rise to it, and this objective indifference translates into an objective explanatory irrelevance of the details of the interactions: including the latter in an explanation would be redundant because many different interactions would yield the same outcome.⁹ Being able to take for granted the existence of emergent properties at one scale in order to explain properties at another scale is arguably a basic requirement for scientific research. If scientists had to build models that captured all scales simultaneously no scientific field would ever have succeeded in explaining anything. We would be trapped in a block universe in which every aspect is inextricably related to every other aspect and our incapacity to separate levels of emergence would leave us cognitively powerless.

The second epistemological consequence derives from the very notion of mechanism-independence: if processes as different in detail as a convection cell and a chemical clock can exhibit the same behavior perhaps mathematical equations can also display that behavior. To set the stage for the argument let’s first give a simplified account of the relation between mathematical models and laboratory experiments. Let’s assume that we want to understand the behavior of the air currents forming the updraft and downdraft of a thunderstorm. We can use a mathematical model of the dynamics of non-viscous fluids that has existed since the eighteenth century: a set of differential equations that relate the properties of density, pressure, internal energy, and velocity to the flow of air. Using these equations we can generate a series of numbers that indicate the course of the modeled...

Table of contents

• Cover
• Half-Title
• Series
• Title
• Contents
• Introduction: Emergence in History
• 1 The Storm in the Computer
• 2 Cellular Automata and Patterns of Flow
• 3 Artificial Chemistries and the Prebiotic Soup
• 4 Genetic Algorithms and the Prebiotic Soup
• 5 Genetic Algorithms and Ancient Organisms
• 6 Neural Nets and Insect Intelligence
• 7 Neural Nets and Mammalian Memory
• 8 Multiagents and Primate Strategies
• 9 Multiagents and Stone Age Economics
• 10 Multiagents and Primitive Language
• 11 Multiagents and Archaic States
• Appendix: Links to Assemblage Theory
• Notes
• Index
• Copyright