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4. Biological and market ecosystems

This section compares biological and idealized market ecosystems, focusing on the differing evolutionarily stable strategies they foster. Idealized markets, as defined here, are computationally-inspired abstractions having parallels with human markets but omitting certain of their complexities and problems. The idea of a computational market is not developed in detail in this paper; see [I,II] for a more concrete discussion.

4.1. Rules of the games

The above analysis of Axelrod's ecosystem began with an examination of the rules of the game. These rules are the constraints within which organisms of that ecosystem must operate. The only fundamental constraint on either biological or human market ecosystems is physical law: any action not forbidden by physical law is in theory possible for players in either ecosystem. However, in order to analyze these ecosystems, it is useful to consider idealized versions in which players operate under additional constraints.

4.1.1. Foundations of biological ecosystems

An example of a physical constraint in biological ecosystems is the conservation of mass and energy. Among animals, the critical resources-biomass and free energy-are downwards conserved: they can be transferred and reduced by the transactions animals are capable of, but not increased. Plants can obtain these resources by photosynthesis; access to sunlight and land area are among their critical limited resources. Biomass and free energy are needed to sustain activity, and can be transferred by predation.

Other constraints in biology (at least if evolutionary history is any guide) include the primary use of proteins for construction of molecular machinery and the use of ribosomes programmed by nucleic acids for their manufacture. These constraints (while not essential to the present discussion) have been shown to limit severely the materials and processes available to biological systems [11,12].

4.1.2. Foundations of idealized markets

In the attempt to characterize an idealized biological ecosystem, it is fortunate that the boundary between living and non-living systems is still fairly clear. In contrast, human markets exist in the context of governmental activity and crime-this makes idealization a larger and riskier task. The following will analyze idealized market ecosystems with simple foundational rules of sorts that can be rigorously enforced in a computational context. This analysis draws heavily on analogies with human markets, while omitting certain difficulties that are excluded by the idealization. Section 6.2 will build on the concept of an idealized market, describing a direct market ecosystem with further differences from human markets; again, these differences are inspired by the possibilities of computational systems.

The basic rules of human markets are typically encoded in legal systems and enforced by attempting to catch and punish violators. In a computational setting, these rules can be enforced as unbreakable "physical" laws. In particular, rights of property (or ownership) can be implemented through encapsulation [I,IV,V]; unforgeable currency and trademarks can be implemented through public key systems [13,14]. The computational entities within such a system could no more steal than human entities can travel faster than light. These abilities can provide the foundations for idealized markets.

An idealized market can contain a great variety of resources, analogous to items ranging from land to airplanes to currency tokens. These resources can be owned by individual entities or groups. No one may take such resources from their owner, but an owner may voluntarily transfer them to any other party. When this occurs in a reciprocal exchange, we refer to the transaction as a trade. Exchanges cannot increase the quantity of any resource-resources are locally conserved across transfers. Productive activity, however, can increase supplies of many resources.

By the rules of the game, anyone may produce new airplanes. Were this the case for currency tokens, however, they would be useless as currency. The rules of an idealized market therefore permit manufacture of a given currency only by a corresponding mint [14]. The effects of minting and introducing new currencies into a market ecosystem are complex [15,16], and are ignored in this paper. The following assumes a currency which is both locally and globally conserved.

A key difference between biological and idealized market ecosystems is the ability to establish and use unforgeable identities. Nature abounds in examples of mimicry and in imperfect attempts to avoid being mimicked [17]. A right to trademark is here defined to be one of the rules of idealized markets. Any entity may establish a new trademarked identity and attach it to that entity's product or place of business. No entity may do this with another's trademark.

4.1.3. Variation and selection

In biology, the replicators are genes, and the variation mechanism is relatively random mutation of an organism's genetic code-its genotype. This does not mean biological variation is random. An organism's phenotype-its body structure, abilities, and so forth-determines its success [18]. An organism's phenotype is decoded from its genotype through a complex translation process. The encoding of a phenotype determines what other phenotypes are reachable by small mutations of a genotype. Therefore this encoding itself can embody heuristics for plausible phenotypic mutations (for example, leg-lengthening mutations interact with the heuristic rule of embryonic development that says, in effect, "do the same to both sides"). As explained in [III], AM and EURISKO employ computational embodiments of this principle (as do genetic algorithms in classifier systems [19]). Nevertheless, biological variation is essentially short-sighted, limited to incremental changes.

The variation and selection mechanisms of market ecosystems are less constrained to local optimization or hill climbing than are those of biological ecosystems. In biological evolution, temporary changes for the worse (temporary travel downhill) will typically lead to extinction through competition from organisms that have not gone downhill. This, together with the small steps possible through typical mutations, greatly limits the ability to reach distant peaks, however high they may be.

Variation in the human marketplace (as in the computational markets described below) frequently results from invention and design by people (or other entities able to plan ahead) who can design coordinated sets of non-incremental changes. Investors in a market (e.g., venture capital firms, in the human market) can take into account arguments for anticipating future success despite present failure, and invest in crossing a valley to get to a higher hill. Biological variation cannot take such arguments into account. By rewarding successful investors, markets select for entities that can facilitate these large jumps. Design and evolution are sometimes presented as mutually exclusive principles, but market ecosystems make use of both.

4.1.4. Success metrics

Success (or "fitness") in an evolutionary process is sometimes defined in terms of long-term survival, but doing so would give little help in analyzing the short term. Also, the goal here is to use evolutionary reasoning to predict the nature of an ecosystem, not to determine what types of creatures will be around at some distant time. For these purposes, a useful criterion of a replicator's success is the magnitude of its ability to affect its environment. This is itself hard to measure, giving reason to seek a metric which is positively correlated with this ability.

In biology, control of biomass and free energy correlates with ability to engage in biological activity. In a market ecosystem, an entity's net worth is the measure of its resources, and hence a rough measure of its potential ability to engage in market activity. The following analyzes strategies for achieving these kinds of success.

4.2. ESSs in biological ecosystems

To survive, animals must eat animals or plants; this happens most often though predation. (Here entities which are eaten, whether animals or plants, are termed "prey".) This is not a synergistic or symbiotic process-the incentives are not toward cooperation between predator and prey. If they were, the participants would both try to facilitate the predatory transaction.

Predator and Prey
Figure 4: Predator and prey. In a biological ecosystem, predators forcibly overcom prey defenses to obtain food. Force and defenses evolve in an arms race, adding overhead to the predatory "transaction"; the lines representing force and defense are accordingly thick. Since attack may come from any direction, defenses are shown surrounding the prey.

Instead, the incentives lead to an arms race in which predators develop better "teeth" and prey develop better "armor". "Teeth" here refers to any mechanism for facilitating predation, such as a cheetah's legs or a dog's nose. "Armor" here refers to any mechanism for avoiding being preyed upon, such as a gazelle's legs or a skunk's scent. An animal without effective "teeth" would starve, and one without effective "armor" would rarely live long enough to reproduce.

Plants are seldom predators, but are often prey. As prey, they develop spines, grit to wear down teeth, and poisons (many are carcinogenic [20]). This has spurred another arms race in which animals have developed large, grinding molars and biochemically complex livers to deal with poisons. Plants compete for light in yet another arms race. This has led to the growth of trees which invest in huge wooden columns for the sake of tallness, to intercept their neighbors' light. Efficient, cooperating plants would instead cover the Earth with grassy or mossy growth; their energy would be stored, not in inert wood, but in sugar, starch, oil, or some other metabolizable reserve.

Predation is a negative-sum relationship: one of the participants benefits, but only at a greater cost to the other. Biological competition is roughly zero-sum in the short term, but spurs a wasteful negative-sum arms race over the long term. Of course, there are many examples of symbiotic, positive sum relationships in biology, but the basic ESS of biology is one of "teeth and armor".

4.3. ESSs in idealized market ecosystems

In order to sustain activity, players in the idealized market must obtain valuable resources, or goods. They can do so through the equivalent of solitary prospecting and manufacture, but the limited competence of any one entity will favor obtaining goods from others-that is, division of labor. Since the rules of the idealized market make it impossible to seize goods by force, one entity can obtain another's goods only by inducing it to engage in a voluntary transaction. An entity which simply gives away goods would steadily lose resources and influence compared to one which does not; such a strategy would not be an ESS. Therefore, the strategy of simply accumulating donated gifts would also not be an ESS.

To induce "gifts", an entity must offer something in exchange. For both sides to want to trade, each must value the goods received more than the goods given. Pair-wise barter deals of immediate mutual benefit are hard to find, and would yield only part of the full potential benefit of trade. Large multi-way deals would yield the full benefit, but are difficult to negotiate. Trade of goods for currency is therefore the expected dominant pattern; currency makes it easier for the equivalent of large multi-way barter deals to occur through separate pair-wise trades.

Each trade in a market can be seen as moving the system toward a condition (one of many possible) in which no transaction that will make both parties better off remains to be done (a condition known as Pareto optimality). Each trade can be seen as a hill-climbing step. Pair-wise barter amounts to hill-climbing across a rough terrain with few available moves; trade in a system with currency and prices amounts to hill-climbing across a smoother terrain with many available moves.

In a trade of goods for currency, the player paying currency in exchange for goods we term a consumer and the one selling goods in exchange for currency we term a producer. A set of producers competing to provide the same (or very similar) goods we term an industry.

Consumer-producer relationships can be contrasted to predator-prey relationships. Producers, unlike prey, will voluntarily seek out those who want to consume what they have, using advertising, distribution networks, and so forth. Consumers, less surprisingly, will seek out producers (in human markets, they do so by reading advertising, traveling to stores, and so forth). The symbiotic nature of this interaction is shown by the interest each side has in facilitating it. Since trade typically increases the viability of both participants, it also raises the viability of the pair considered together as an entity.

There are many negative-sum pair-wise relationships in even an ideal marketplace-the most common is competition among producers in the same industry. In judging the nature of the market as a whole, however, it is important to note that when producers compete, each is competing to do a better job of cooperating with the rest of the world, of attracting consumers into beneficial trade relationships.

In the absence of perfectly-effective rules to prevent it (which seem difficult to define, even in the computational domain), markets will suffer from fraud. A fraudulent transaction occurs when a producer induces a consumer to pay for an undesired good under false pretenses.

It is worth distinguishing fraudulent trades from those in which (in light of later information) a different alternative would have yielded a better product or a better price. Non-optimal trades are universal, given imperfect knowledge (which will be ubiquitous in computational markets), but this observation would argue against the use of market mechanisms only if someone could find a better way to use imperfect knowledge. Unlike fraudulent trades, non-optimal trades are still symbiotic; they merely fall short of an imagined perfection.

The possibility of fraud, together with the difference in quality among available deals, creates an incentive for consumer wariness. Wary consumers will in turn create an incentive for producers to avoid fraud, and for them to offer high quality (though not necessarily optimal) deals. The resulting ESS is to be "productive and wary"-wary as a consumer and productive and honest as a producer-for many of the same reasons that "nice and retaliatory" is Axelrod's ESS. Given a variety of strategies in a brand-new market ecosystem, one can expect that fraudulent producer strategies will initially profit at the expense of non-wary consumer strategies. As a result, wary consumers will grow in importance, driving out fraudulent producer strategies. These considerations will even drive out honest producer strategies which are noticeably less productive than their competitors. At a finer level of resolution, of course, there will be as many detailed strategies for being productive and wary as there are niches for entities in the market.

How can a consumer be effectively wary? The producer-consumer relationship is similar to an iterated prisoner's dilemma. If a producer fraudulently sells a worthless product, he is "defecting" on the arrangement. A wary consumer must take the trouble to notice this defection in order to retaliate (for example, by doing business elsewhere and warning others away). Checking for a defection can be expensive, however, and consumers are frequently in non-iterated situations. Reputation agencies like Consumer Reports can lower the cost of wariness and make it more effective by putting the producer in an iterated situation with the community as a whole (see the discussion of reputation agents in [I]). Trademarking of ser- vices and products enables producers to establish valuable reputations. The lack of this mechanism in biology [17] contributes to the relative sparseness of symbiosis there.

4.4. Food webs and trade webs

Biological and market ecosystems both contain a mixture of symbiotic and negative-sum relationships. This paper argues that biological ecosystems involve more predation, while idealized market ecosystems involve more symbiosis. Indeed, one can make a case that this is so even for human market ecosystems-that biological ecosystems are, overall, dominated by predation, while market ecosystems are, overall, dominated by symbiosis.

In human markets (as in idealized markets) producers within an industry compete, but chains of symbiotic trade connect industry to industry. Competition in biology likewise occurs most often among those occupying the same niche, but here, it is predation that connects from niche to niche. Because of the lack of reputations and trademarks, symbiosis in biology occurs most often in situations where the "players" find themselves in a highly-iterated game. In the extreme, the symbiotic system itself becomes so tightly woven that it is considered a single organism-as with lichens composed of fungi and algae, or animals composed of eukaryotic cells containing mitochondria. Predation, of course, links one symbiotic island to the next.

Ecology textbooks show networks of predator-prey relationships-called food webs-because they are important to understanding ecosystems; "symbiosis webs" have found no comparable role. Economics textbooks show networks of trading relationships circling the globe; networks of predatory or negative-sum relationships have found no comparable role. (Even criminal networks typically form cooperative "black markets".) One cannot prove the absence of such spanning symbiotic webs in biology, or of negative-sum webs in the market; these systems are too complicated for any such proof. Instead, the argument here is evolutionary: that the concepts which come to dominate an evolved scientific field tend to reflect the phenomena which are actually relevant for understanding its subject matter.

4.5. Is this picture surprising?

Nature is commonly viewed as harmonious and human markets as full of strife, yet the above comparison suggests the opposite. The psychological prominence of unusual phenomena may explain the apparent inversion of the common view. Symbiosis stands out in biology: we have all heard of the unusual relationship between crocodiles and the birds that pluck their parasites, but one hears less about the more common kind of relationship between crocodiles and each of the many animals they eat. Nor, in considering those birds, is one apt to dwell on the predatory relationship of the parasites to the crocodile or of the birds to the parasites. Symbiosis is unusual and interesting; predation is common and boring.

Similarly, fraud and criminality stand out in markets. Newspapers report major instances of fraud and embezzlement, but pay little attention to each day's massive turnover of routinely satisfactory cereal, soap, and gasoline in retail trade. Crime is unusual and interesting; trade is common and boring.

Psychological research indicates that human thought is subject to a systematic bias: vivid and interesting instances are more easily remembered, and easily remembered instances are thought to be more common [21]). Further, the press (and executives) like to describe peaceful competition for customer favor as if it were mortal combat, complete with wounds and rolling heads: again, vividness wins out. These factors go far to explain the common view of market and biological ecosystems.

For contrast, imagine that symbiosis were as fundamental to biology as it is to markets. Crocodiles would not merely have birds to pick their teeth, symbiotic bacteria in their guts, and the like; they would have symbiotes to provide them with orthodontia and tooth crowns, to say nothing of oral surgery, heart surgery, and kidney transplants, as well as shoes, clothing, transportation, housing, entertainment, telecommunications, massage, and psychiatric care.

Likewise, imagine that predation were as fundamental to markets as it is to biology. Instead of confronting occasional incidents of theft in a background of trade, one would be surrounded by neighbors who had stolen their cars from dealers who had mounted an armed assault on factories in Detroit, which in turn had grabbed their parts and equipment by pillaging job-shops in the surrounding countryside. So-called "hostile corporate takeovers" would involve, not purchase of shares of ownership from willing stockholders, but a sudden invasion of offices by an armed gang.

Biological ecosystems have evolved creatures and environments of great beauty and complexity, and they exhibit a grand spontaneous order, but that order is quite different from the synergistic, symbiotic order of the market. If the aim in building computational ecosystems were to maximize their beauty and complexity, biology might be an excellent model. Given the goal of building a computational ecosystem which will organize itself to solve problems, however, one should seek a system that fosters the cooperative use of specialized knowledge and abilities. Market ecosystems seem better suited to this.

4.6. Are markets just biological?

It might be objected that the mechanisms which facilitate widespread symbiosis in market ecosystems are achievable within the rules of biological ecosystems. After all, these rules do not forbid organisms from pooling their resources to defend against predators or from establishing reputation and trademark systems. Indeed, this has been done. Through such institutions as laws, courts, banks, and trademarks, talking primates have taken their species through the transition from "nature, red in tooth and claw" to an industrial civilization spanning a planet. Though this has been achieved within the rules of biology, biological rules do not deserve the credit, any more than a machine language deserves credit for the virtues of Lisp.

This comparison of biological and market ecosystems suggests some of the strength of markets as a model for computation. The following examines a simpler computational ecosystem and considers whether market mechanisms would be useful in similar systems.

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