This page describes the organizational forces that limit change. It explains how to overcome them when necessary.
This page uses an example to illustrate how:
This page uses the example of HP's printer organization freeing itself from its organizational constraints to sell a printer targeted at the IBM pc user.
The constraints are described.
The techniques to overcome them are implied.
Egg and sperm asymmetry
SummaryThis page describes the consequences of the asymmetries caused by eggs having to include resources required for the development is a phase during the operation of a CAS agent. It allows for schematic strategies to be iteratively blended with environmental signals to solve the logistical issues of migrating newly built and transformed sub-agents. That is needed to achieve the adult configuration of the agent and optimize it for the proximate environment. Smiley includes examples of the developmental phase agents required in an emergent CAS. In situations where parents invest in the growth and memetic learning of their offspring the schematic grab bag can support optimizations to develop models, structures and actions to construct an adept adult. In humans, adolescence leverages neural plasticity, elder sibling advice and adult coaching to help prepare the deploying neuronal network and body to successfully compete.
of sexually reproduced organisms while sperms do not.
The impact of this asymmetry is to force alternative strategies on males and females. The strategies are outlined.
IntroductionWhen complex adaptive system (
This page introduces the complex adaptive system (CAS) theory frame. The theory is positioned relative to the natural sciences. It catalogs the laws and strategies which underpin the operation of systems that are based on the interaction of emergent agents.CAS)
John Holland's framework for representing complexity is outlined. Links to other key aspects of CAS theory discussed at the site are presented.
Plans are interpreted and implemented by agents. This page discusses the properties of agents in a complex adaptive system (CAS).agents follow the strategy of
It then presents examples of agents in different CAS. The examples include a computer program where modeling and actions are performed by software agents. These software agents are aggregates.
The participation of agents in flows is introduced and some implications of this are outlined.
This page discusses the strategy of modularity in a complex adaptive system (CAS). The benefits, mechanism and its emergence are discussed.modularizing themselves they allow their
Plans emerge in complex adaptive systems (CAS) to provide the instructions that agents use to perform actions. The component architecture and structure of the plans is reviewed.schemata far more freedom for conflicts within the plan. In separated compartments different states can exist. So within particular compartments these states can, for example, include actions to modify the access to the schemata. The process ensuring that only appropriate schematic sequences are accessible to agents.
One consequence of this is that initiation of a new germ-line, a master copy of the schematic structures is maintained for reproduction of offspring. There will also be somatic copies which are modified by the operational agents so that they can represent their current state. cell is probably impossible from a differentiated somatic, Schematic structures which are used to support the operation of the agent. They are modified as the agent's state changes unlike the germ-line schemata. cell. Instead germ-line cells are maintained in an initialized state.
As a result multi-cellular organisms are initiated through a
This page reviews the implications of reproduction initially generating a single child cell. The mechanism and resulting strategic options are discussed.single cell bottleneck.
The complex adaptive system (CAS) nature of a value delivery system is first introduced. It's a network of agents acting as relays.environments where it is has also been advantageous to have a highly flexible plan
The critical nature of hub agents and the difficulty of altering an aligned network is reviewed.
The nature of and exceptional opportunities created by platforms are discussed.
Finally an example of aligning a VDS is presented.
Plans change in complex adaptive systems (CAS) due to the action of genetic operations such as mutation, splitting and recombination. The nature of the operations is described.genetic operators are applied to schemata supplied by two individuals. Here too the initial state of the new organism must be setup, and resource
Flows of different kinds are essential to the operation of complex adaptive systems (CAS).flows connected to it.
Example flows are outlined. Constraints on flows support the emergence of the systems. Examples of constraints are discussed.
The provisioning of the resources is costly and, with the single cell constraint, these must be gathered up and associated with a structure that ensures the initialized state exists. Eggs provide this environment. They are supplied with a rich set of resources and large amounts of RNA (RNA), a polymer composed of a chain of ribose sugars. It does not naturally form into a paired double helix and so is far less stable than DNA. Chains of DNA are converted by transcription into equivalently sequenced messenger m-RNA. RNA also provides the associations that encode the genetic code. Transfer t-RNAs have a site that maps to the codon and match the associated amino-acid. Stuart Kauffman argues that RNA polymers may be the precursor to our current DNA based genome and protein based enzymes. In the adaptive web framework's (AWF) Smiley we use a similar paradigm with no proteins.
that can rapidly initiate the
This page reviews the catalytic impact of infrastructure on the expression of phenotypic effects by an agent. The infrastructure reduces the cost the agent must pay to perform the selected action. The catalysis is enhanced by positive returns.early proteins that will provide catalytic, an infrastructure amplifier. maintenance of the early state. The resources include the mitochondria are the energy molecule generating production functions of eukaryotic cells. They are vestigial blue-green bacteria with their own DNA and infrastructure. Unlike stand-alone bacteria they also use the eukaryotic host DNA and infrastructure for some functions. The high energy molecules are nucleotides with a high energy phosphate bond. The most used high energy molecule is Adenosine-tri-phosphate. . Pinker notes that the mitochondria from the egg do not tolerate additional mitochondria from the sperm ensuring the asymmetry of the infrastructure delivered to support the new organism.
The support of these eggs affects the provider in a number of ways:
This page reviews the strategy of setting up an arms race. At its core this strategy depends on being able to alter, or take advantage of an alteration in, the genome or equivalent. The situation is illustrated with examples from biology, high tech and politics.amplifying evolutionary arms race.