Kevin Aylward B.Sc.
This paper forms a basic outline of the main concepts associated with General Replicator Theory.
GRT is a combined meme-gene Replicator theory and transparently deals with meme traits or gene traits. Since the human Replicator can indeed replicate its gene traits by replicating itself and replicate its meme traits directly, many arguments can simple ignore whether one is discussing gene or meme traits. That is, it matters little that traits are Lamarckian or non-Lamarckian. Parents can pass on genes and memes to children, so in many cases, there is simple no need to distinguish between the two methods. It is simply immaterial to the big picture whether, for example, a supposed attractiveness to breast size is due to culture memes or biological genes, its just a trait that gets replicated and passed on. General Replicator Theory just doesn't care. The point is that, however it is actually implemented, it is only a result of the basic Darwinian axioms, that is, variation, selection and replication.
Replicator theory is a statistical theory. It uses means, standard deviations, and probability distributions. This papers glosses over these issue for the purposes of simplicity. Many initial objections to some of the claims presented in these papers are the result of approximations made simply to simplify arguments. Replicator theory is not limited to such approximations.
The most common assumption used in the papers is of continuously advantaged traits. This is not true in general. The assumption is made only to keep the arguments simple. In most cases it is enough to understand the core behavior. In practice, replication rates, or trait fitness continually changes with the environment, allowing for a wide range of traits to co-exist.
Simple Darwinian Model
The following forms the core, simplified argument that underpins evolution of memes and genes.
Consider insects being born with random colours, e.g. brown, pink, green, red...Now suppose that there are birds in the region that feed on these insects. Further suppose that this particular region (environment) is a grass field. If the reasonable assumption is made that any green insects are harder to find and therefore be eaten, it can be rationalized that the green insects might have a better probability of survival, and therefore to pass on that green trait to offspring, then the other colored insects would. Application of the theory, to be described, mandates, that in this particular idealized situation, after sufficient generations, mostly green insects will be observed.
This model is only for the purposes of explaining basic core behavior, not the full details. Its a learn to walk before run concept.
An immediate notion arisen from the above argument is the idea that a well selected trait is a selfish trait. That is, the observed feature of well selected traits is to maximize itself, usually by maximizing the numbers of its Replicator. That is, in the above, the net result was "as if" the colour trait "made" itself green in order to survive, i.e. took action in its own interest, although in reality, it obviously didn't. It can't think. However, explanations are greatly simplified by simply pretending that traits take such "thinking" action as to maximize themselves, since the final result is is the same as if they did. They are thus referred to as selfish.
Throughout theses papers specific principle, derived from the axioms, will be used ruthlessly. These principles must be kept in mind throughout.
1 Replicators replicate, and do so ruthlessly.
2 What is mostly observed, is that which replicates the most.
3 Replicators act to maximize their traits numbers, usually be maximizing themselves.
Basic mathematical definitions are made:
1 Definition - a trait is a Replicant and is any entity that is replicated.
2 Definition - a Replicator is any physical machine that has traits, and can replicates its traits.
3 Definition - a meme trait is a virtual trait of a physical Replicator.
4 Definition - A moral is a meme trait of a Replicator, such that that trait attempts to maximize a Replicators replication numbers.
5 Definition - an emotion is a conscious experienced trait of a Replicator, such that that trait attempts to maximize its replication numbers.
6 Some special Replicators are identified.
7 General properties of traits and Replicators are derived.
8 Moral traits are identified as being programmed by the environment.
6 Moral traits are identified as selecting what particular Emotion trait is invoked for a particular environment condition.
8 Emotions are identified as invoking behavior.
9 A behavior loop is thus established as environment->morals->emotion->behavior->environment.
10 The behavioral loop illustrates a core process for the general adaptability of humans to general environments.
11 Morals and Emotions are shown to be self referral, thereby explaining why morals can exist that do not maximize human numbers.
These papers may be freely copied only for non commercial use,
provided full credit is given to the author.
© Kevin Aylward 2003 - all rights reserved