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.
Meaning and consciousnessPhilosophers have struggled to explain the operation of the conscious brain for centuries. Different proposals including: dualism where a mind and brain operate separately, and epiphenomenalism where mental states are just effects of operating neurons, specialized eukaryotic cells include channels which control flows of sodium and potassium ions across the massively extended cell membrane supporting an electro-chemical wave which is then converted into an outgoing chemical signal transmission from synapses which target nearby neuron or muscle cell receptors. Neurons are supported by glial cells. Neurons include a:
Psychologists asked 'how does a baby bootstrap its understanding of the world so that it can rapidly learn about its physical and social environment'?
Mathematicians, scientists and philosophers focused efforts on artificial intelligence expecting it to
This page discusses the mechanisms and effects of emergence underpinning any complex adaptive system (CAS). Physical forces and constraints follow the rules of complexity. They generate phenomena and support the indirect emergence of epiphenomena. Flows of epiphenomena interact in events which support the emergence of equilibrium and autonomous entities. Autonomous entities enable evolution to operate broadening the adjacent possible. Key research is reviewed.emerge from work on computer systems. The apparent optimism that such emergence must occur as the computer systems become more complex seems far-fetched.
This page reviews the implications of selection, variation and heredity in a complex adaptive system (CAS). The mechanism and its emergence are discussed.Evolution provides an alternative framework for supporting the emergence of meaning. Adaptive
Read Montague explores how brains make decisions. In particular he explains how:neuron networks representing
Agents use sensors to detect events in their environment. This page reviews how these events become signals associated with beneficial responses in a complex adaptive system (CAS). CAS signals emerge from the Darwinian information model. Signals can indicate decision summaries and level of uncertainty.sensory inputs, assumed position, potential mediated actions and modulating associations have emerged under selection pressure from the action of
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. The association of actions with signals, emergent
The agents in complex adaptive systems (CAS) must model their environment to respond effectively to it. Samuel modeling is described as an approach.models of goals, and strategic values; allows models and physical states to become associated. Further the reproduction of
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.schematic plans ensures that the models and associations are maintained over generations of the phenotypic is the system that results from the controlled expression of the genes. It is typically represented by a prokaryotic cell or the body of a multi-cell animal or plant. The point is that the genes provide the control surface and the abstract recipe that has been used to generate the cell.
Plans are interpreted and implemented by agents. This page discusses the properties of agents in a complex adaptive system (CAS).agents.
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.
Terrence Deacon explores how constraints on dynamic flows can induce emergent phenomena which can do real work. He shows how these phenomena are sustained. The mechanism enables the development of Darwinian competition.Constrained interacting dynamic flows underpin the evolutionary framework, and enable end-directedness.
This emergent architecture is not deterministic, argues that given specific conditions a specific outcome will occur. , so free will is the subjective assessment of one's ability to make decisions and perform independent actions. Philosophers note that causal chains linking physical phenomena with conscious decisions would undermine the idea of independent free will. RSS views the architecture of CAS agency as requiring indirect associations between phenomena and agent's models. Evolution captures these associations within the genetic structures of the emergent agents, removing any epistemological or complementarity constraints. Sapolsky concludes that this evolved agency severely limits the potential contribution of free will. is not constrained, and there is no problem of causal closure, argues that all physical effects can be ultimately reduced to physical causes. If this is true it is argued dualistic mental events can have no effect.
. The pressure on mobile agents to decide effectively in the competition for resources ensures evolution's effects. Pre-adaptations, initially termed pre-adaptation refers to the coopting of some function for a new use. and adaptations in evolutionary biology is a trait that increased the number of surviving offspring in an organism's ancestral lineage. In Deacon's conception of evolution an adaptation is the realization of a set of constraints on candidate mechanisms, and so long as these constraints are maintained, other features are arbitrary.
captured schematically by
Richard Dawkin's explores how nature has created implementations of designs, without any need for planning or design, through the accumulation of small advantageous changes.natural and
This page describes the consequences of the asymmetries caused by genotypic traits creating a phenotypic signal in males and selection activity in the female - sexual selection.sexual selection are enough.
The impact of this asymmetry is to create a powerful alternative to natural selection with sexual selection's leverage of positive returns. The mechanisms are described.
This process is summarized in our vision 'I act, therefore I think'.