include ideas, beliefs, habits, morals, fashions, designs, techniques, jokes,
and more. Any pattern which can spread via imitation is a meme, even if its
human host cannot articulate it or is unaware of its existence.
It is important to recognize that the replicators of human culture are memes, not people. The lack of this distinction has led to the unfortunate confusion called "social darwinism". Our ability to change our minds allows cultural evolution to proceed not by selection of humans, but, as Karl Popper says, by "letting our theories die in our stead" .
Recognition of the evolutionary nature of human culture has inspired computational proposals for aiding the spread of memes among humans [25,26] and for establishing a memetic ecosystem among software entities [VII]. The memes making up human culture are diverse, as are their variation and selection mechanisms. Rather than studying human culture as a single, generic kind of ecosystem, it makes more sense to view it as composed of several interacting memetic ecosystems.
For example, Karl Popper describes science in evolutionary terms . The replicators of science are theories, and their evolution proceeds through a process of conjecture and refutation, that is, variation and selection. The selection criteria include the requirement that a theory be both falsifiable and not actually falsified. (Falsifiable means that if it were false, it could be refuted by experiment.) In science only falsifiable but true theories are ESSs-any theory which is false either can be refuted, or is not falsifiable, and so is subject to rejection. In memetic systems whose replicators are theories, but which apply other selection criteria, theories which are not true may nevertheless be ESSs. Idealizations of scientific inquiry have also inspired computational ideas and systems [27,28].
6.1. Market memes and the indirect market In this paper, the memetic systems of interest are those that shape activities in markets, here called market memes. They include ideas that shape strategies for production, organization, marketing, investment, and much more. Market memes can be embodied in individuals or in groups such as firms, but their mechanisms of selection are indirect, working through the human brain.
Money flows not to successful market memes, but to their hosts. No matter how much money it brings in, a meme is unable to rent more brain space-indeed, it cannot even protect itself from being displaced. Entities directly interacting with an ideal market can own assets which cannot be seized; memes can own no such assets.
Market memes can replicate by spreading from human to human, but for some, this process is difficult. Complex market memes, such as business management skills or organizational patterns, are hard to communicate without introducing great variation. Biological systems can generate and test many small variations of a genetic pattern, replicating the more successful, but human markets can seldom do the same with organizations.
Meta-market memes are memes responsible for generating new market memes; an example would be an idea for how to educate better entrepreneurs. When their results are successful, however, no reward reliably propagates back to the memes responsible. Since meta-market memes do not receive credit for their efforts, people are led to underinvest in them.
Thus, market memes are able neither to benefit directly from their own successes, nor (in general) to replicate and pass on their successful characteristics. These defects in the system for creating, expanding, and replicating market memes make their evolution a slow and clumsy process. Successful practices are recognized and imitated, but quite imperfectly.
Although institutions such as patents, trade secrets, and copyrights attempt to strengthen feedback loops, there is only an indirect coupling between market forces and the replicators of the human market-this system thus constitutes what has here been called an indirect market. In software, however, it seems possible to achieve a direct market-an ecosystem in which the replicators that dominate the evolutionary process are directly rewarded by market success.
6.2. Direct market ecosystems In a direct market implemented in software, a successful heuristic or strategy can directly acquire more processing power and can replicate itself with small variations if it chooses. In these ways, a direct market resembles the biological ecosystem more than it does human markets. In addition, meta-heuristics can generate new software entities from old ones (that give access to the requisite information) by plausible mutation and recombination of the patterns that embody them. The generation of new entities will generally occur only after the participants have negotiated a division of any later rewards (a portion of their shares will, in turn, propagate back to their own creators). These mechanisms directly reward (and thereby encourage) "meta-market" activities, such as inventing new forms of business.
Direct markets have other advantages over human markets. In human markets rules against theft and extortion are enforced imperfectly through mechanisms such as police, courts, and jails. In software, however, these rules can be like "laws of physics". Human markets are plagued by negative externalities (such as air pollution) resulting from the unowned and non-local nature of many common resources (such as air). In software, it seems that these problems can be largely avoided. The basic resources of computation-processor time, memory space, and communications bandwidth-can be allocated without negative externalities [II]. No commons seem needed in computational ecosystems; computational environments need have no analogues of air, water, lines of sight, or rainforests.
The discussion thus far has assumed that computational markets are "idealized markets", in the sense introduced in Section 4.1.2, operating under only simple, foundational rules, preventing non-voluntary transactions analogous to theft. Human markets, however, operate under a wider range of less rigorously enforced rules, imposed by a variety of legal and regulatory institutions. The next section examines whether such institutions might be of use in computational markets.