Potential of biologically inspired computing
Summary
This web page reviews opportunities to enhance computing theory
and practice by using biological mechanisms and 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.
John Holland's framework for representing complexity is
outlined. Links to other key aspects of CAS theory
discussed at the site are presented.
CAS) theory.
Introduction
Using biology's computational model as the future of computing
is proposed to:
Today the
Internet engineering task force (IETF, the internet engineering task force controls the processes that manage the architecture of the internet. )
process and the Internet show how effective the parallel
computing model can be. The IETF's request for comment
(RFC) specification process is highly analogous to 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 operations on a 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 database of RFCs. The
fitness of each new generation of protocol specification is
tested by deployment through multiple parallel
implementations. When these are found to operate
satisfactorily, and the RFC and deployed systems are accepted as
being useful, the RFC becomes a standard track protocol and
becomes represented widely in Internet infrastructure.
The set of networking services and protocols that are covered by
the IETF's open RFC process have grown broadly as the early platform Walter Shewhart's iterative development process is found in many
complex adaptive systems (CAS).
The mechanism is reviewed and its value in coping with random
events is explained.
iterative construction, deployment and
revision cycle, enabled This web page reviews opportunities to find and capture new
niches based on studying fitness landscapes using complex
adaptive system (CAS) theory.
niche
expansion.
The robustness and increased performance of massively parallel
computing applications is demonstrated by Google search.
Leveraging the opportunity that a networked web of HTML pages
offered, Google's capture, analysis and search processes are
designed to leverage racks of computers to break up the search
problem into parallel activities. But the algorithms are
still designed, implemented and operated by software
engineers.
Google deploys its map, reduce applications over a distributed
storage infrastructure that ensures the applications are close
to a copy of the data they are working with. Biological
systems use cell division to generate a similar effect.
Since 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.
John Holland's framework for representing complexity is
outlined. Links to other key aspects of CAS theory
discussed at the site are presented.
CAS)
based Plans are interpreted and implemented by agents. This page
discusses the properties of agents in a complex adaptive system
(CAS).
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.
agents replicate common 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 data, programs with a CAS
architecture, such as This page describes the Adaptive Web framework (AWF) test system
and the agent programming framework (Smiley) that supports its
operation.
Example test system statements are included.
To begin a test a test statement is loaded into Smiley while
Smiley executes on the Perl
interpreter.
Part of Smiley's Perl code focused on setting up the
infrastructure is included bellow.
The setup includes:
- Loading the 'Meta file'
specification,
- Initializing the Slipnet,
and Workspaces and loading them
- So that the Coderack
can be called.
The Coderack, which is the focus of a separate
page of the Perl frame then schedules and runs the codelets
that are invoked by the test statement structures.
the adaptive test
framework, can be deployed over a distributed storage
infrastructure, such as HADOOP is an open source implementation of the 'big data' distributed file system architecture used by Google to support its map-reduce programs. The map-reduce programs construct associations between vast numbers of web pages and typical search terms. .
HADOOP can then be leveraged to help ensure that only light
weight 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.
signals need be sent between
the computers on which the agents are distributed.
The general computing paradigm does not reflect biology in its
architecture. While the business activities supporting
product 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.
are This page discusses the mechanisms and effects of emergence
underpinning any complex adaptive system (CAS). Key research is
reviewed.
emergent and adaptive the
application paradigm is not. Google not withstanding the
general approach still reflects Von Neumann's arguments, John was a brilliant Hungarian mathematician who published the earliest paper specifying architecture for digital computing. It ensured this computing architecture was not patentable. The architecture has a central processing unit (CPU), random access storage addressable by the CPU and a sequencer. The architecture encourages a serial software architecture that matches the logic of the sequencer and processing operations on program and data. Von Neumann, his history, computing architecture and some alternative architecture are reviewed by Melanie Mitchell.
with:
- A central processing unit (CPU) resource supplied with
instructions and data to process. Biology uses a
massively distributed processing model which reduces the CPU
access bottleneck. Consequently biological operations
do not have to limit competitive invocations, and are less
likely to need transactional is an operation which guarantees to complete a defined set of activities or return to the initial state. For a fee the postal service will ensure that a parcel is delivered to its recipient or will return the parcel to the sender. To provide the service it may have to undo the act of trying to deliver the parcel with a compensating action. Since the parcel could be lost or destroyed the service may have to return an equivalent value to the sender.
protection.
- Instructions processed in series, unless a jump is
executed.
- Applications are designed to directly implement specific
functional requirements. Maintenance issues and
engineering quality strategies including limited
connections, reuse, directness and information hiding have
promoted
Bertrand Meyer develops arguments, principles and strategies for
creating modular software. He concludes that abstract data
types and inheritence make object orientation a superior
methodology for software construction. Complex adaptive
system (CAS) theory suggests agents provide an alternative strategy
to the use of objects.
object oriented methods and
tool chains. Biology uses Rather than oppose the direct thrust of some environmental flow agents
can improve their effectiveness with indirect responses.
This page explains how agents are architected to do this and
discusses some examples of how it can be done.
indirect methods which encourage
emergence.
- Testing is applied to the operation reflecting the design
of the modules and the requirements of the system. The
testing process aims to select for
This web page reviews opportunities to find and capture new
niches based on studying fitness landscapes using complex
adaptive system (CAS) theory.
fitness,
filtering instances of the implementation which fail the
criteria. This is an This page reviews the implications of selection, variation and
heredity in a complex adaptive system (CAS).
The mechanism and its emergence are
discussed.
evolutionary
selection
process, but it acts directly on the source code
instead of the schematic structures, such as the engineer's
understandings of the requirements and designs. The This page describes the Adaptive Web framework (AWF) test system
and the agent programming framework (Smiley) that supports its
operation.
Example test system statements are included.
To begin a test a test statement is loaded into Smiley while
Smiley executes on the Perl
interpreter.
Part of Smiley's Perl code focused on setting up the
infrastructure is included bellow.
The setup includes:
- Loading the 'Meta file'
specification,
- Initializing the Slipnet,
and Workspaces and loading them
- So that the Coderack
can be called.
The Coderack, which is the focus of a separate
page of the Perl frame then schedules and runs the codelets
that are invoked by the test statement structures.
Adaptive web framework (AWF) testing
infrastructure (2)
explores more biologically aligned alternatives.
- The released application then competes in the
marketplace. Finally selection has an impact on the
schematic structures.
The application does not respond flexibly to the
situation. It expects specific input 'signals' and uses
these to transition between its predetermined set of
states. If the application is given unexpected inputs it
can only reject them. If its understanding of the real
world is flawed when it detects a mismatch at best it can
perform error recovery to return to a defined state.
A biologically inspired computing architecture would have
improved To benefit from shifts in the environment agents must be flexible. Being
sensitive to environmental signals
agents who adjust strategic priorities can constrain their
competitors.
flexibility and should
enable adaptive The agents in complex adaptive
systems (CAS) must model their
environment to respond effectively to it. Samuel
modeling is described as an approach.
learning. it
would include:
Each of these aspects turns out to be complex.
Biological sensors
Real world sensors have to detect relatively low level aspects
of the physical world. The input signals are typically multi-modal, real world effects include sound, light, touch etc. at the same time. so multiple
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.
sensors will detect aspects of a
signal. Physiological psychologists have studied
how animals perform this type of sensing. Vast
collections of networked sensors deployed peripherally detect
the low level aspects of each signal. Detected signals are
flowed through layers of a network where coincidences are
identified and used to associate the aspects of the signals with
potential higher level effects of the real world. At the
highest levels these associations have been integrated into a
multi-mode association which is related to the animals
understanding of its own situation and that of its immediate The complex adaptive system (CAS)
nature of a value delivery system is first introduced. It's a network
of agents acting as relays.
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.
environment.
Peripheral sensors can include Representing state in emergent entities is essential but
difficult. Various structures are used to enhance the rate
and scope of state transitions. Examples are
discussed.
mechanisms
to:
- Resolve basic aspects of the signal locally so that only
highly significant attributes are passed on to other agents
in the network.
- Align detector deployment with local aspects of the
environment.
Use of
biological structures and procedures to improve the fitness of
designs
The development 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 structures
in the form of genetic and neuronal, 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: - Receptive element - dendrites
- Transmitting element - axon and synaptic terminals
- Highly variable DNA schema using transposons.
data structures introduces the possibility of supporting human Plans are interpreted and implemented by agents. This page
discusses the properties of agents in a complex adaptive system
(CAS).
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.
agents with Tools and the businesses that produce them have evolved
dramatically. W Brian Arthur shows how this occurred.
tools
that utilize schematic This page discusses the interdependence of perception and
representation in a complex adaptive system (CAS). Hofstadter
and Mitchell's research with Copycat is
reviewed.
representations
and support perceptions and This web page reviews opportunities to find and capture new
niches based on studying fitness landscapes using complex
adaptive system (CAS) theory.
exploration
of the adjacent possible.
Already wikis provide support for the shared development of 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.
representations - most notably wikipedia. The
Walter Shewhart's iterative development process is found in many
complex adaptive systems (CAS).
The mechanism is reviewed and its value in coping with random
events is explained.
iterative updating of this data is an
area of focus for the wiki community, but it does not include
use of This page reviews the implications of reproduction initially
generating a single child cell. The mechanism and
resulting strategic options are discussed.
a single cell developmental
bottleneck for initializing the distributed 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. state.
Potentially the somatic This page discusses the interdependence of perception and
representation in a complex adaptive system (CAS). Hofstadter
and Mitchell's research with Copycat is
reviewed.
representation,
could include perceptions of the: active This page looks at how scenarios allow people to relate to the
possible evolution of the business and its products and
services. The Long view process is highlighted.
Value based customer
segmentation is reviewed. Keirsey's psychological
categorization and 'crossing
the chasm' are highlighted.
Three alternate systems are framed as long view scenarios (1)
development of a billing
mediation business, (2) development of the Grameen Bank the
first micro loan bank and (3) some classic chess games.
Some of the scenarios will be referenced in the SWOT and planning
pages of this frame. In particular the complex adaptive
system (CAS) goals used will be
referenced by the planning pages schemetic
goals.
situation, First describes the dynamic
nature of any complex adaptive system (CAS).
It then introduces the broad effects of change
which includes opportunities and risks/uncertainties.
As a CAS grows opportunities become undermined so they must be acted on
quickly.
Uncertainties are also transformed
and relayed by the dynamic network. In particular
the recombination of current and new ideas brought in from the
network is discussed.
target
niches, This page looks at schematic structures
and their uses. It discusses a number of examples:
- Schematic ideas are recombined in creativity.
- Similarly designers take ideas and
rules about materials and components and combine them.
- Schematic Recipes help to standardize operations.
- Modular components are combined into strategies
for use in business plans and business models.
As a working example it presents part of the contents and schematic
details from the Adaptive Web Framework (AWF)'s
operational plan.
Finally it includes a section presenting our formal
representation of schematic goals.
Each goal has a series of associated complex adaptive system (CAS) strategy strings.
These goals plus strings are detailed for various chess and business
examples.
operational plans, The page reviews how complex systems can be analyzed.
The resulting analysis supports evaluation of system
events.
The analysis enables categorization of different events into
classes.
The analysis helps with recombination of the models to enable
creativity.
The page advocates an iterative approach including support from models.
analysis stores and The page describes the SWOT
process. That includes:
- The classification
of each event into strength weakness opportunity and
threat.
- The clustering
process for grouping the classified events into goals.
- How the clusters
can support planning and execution.
Operational SWOT matrices and clusters from the Adaptive Web
Framework (AWF) are included as examples.
SWOT, and The complex adaptive system (CAS)
nature of a value delivery system is first introduced. It's a network
of agents acting as relays.
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.
value
delivery system;
Web frames
As a start, in line with our understanding of cognitive is the ability to orchestrate thought and action in accordance with internal goals according to Princeton's Jonathan Cohen. processing,
AWF's event processor supports the
construction of frames of tailored
web pages. Each page of a frame aims to include only
information, and links, relevant to the specific focus of the
web page. A frame of pages allows different points of
focus to be constructed, each linked together to provide the
reader with a paced and, hopefully, comprehensive
perspective.
Networks
of agents with shared state
Agent-based programming, as instantiated in AWF's This page describes the Adaptive Web framework (AWF) test system
and the agent programming framework (Smiley) that supports its
operation.
Example test system statements are included.
To begin a test a test statement is loaded into Smiley while
Smiley executes on the Perl
interpreter.
Part of Smiley's Perl code focused on setting up the
infrastructure is included bellow.
The setup includes:
- Loading the 'Meta file'
specification,
- Initializing the Slipnet,
and Workspaces and loading them
- So that the Coderack
can be called.
The Coderack, which is the focus of a separate
page of the Perl frame then schedules and runs the codelets
that are invoked by the test statement structures.
adaptive test framework extends the
processing of events to adapting to them with agents which
emerge from schematic codelet
aggregates.
Automated genetic algorithms provide a vision for increasing the
flexibility and creativity of designed systems.
Infrastructure
supporting adaptive coordinated deployment of the network of
agents
Douglas
Hofstadter and Melanie Mitchell's This page discusses the interdependence of perception and
representation in a complex adaptive system (CAS). Hofstadter
and Mitchell's research with Copycat is
reviewed.
Copycat
This page describes the Copycat
Coderack.
The details of the codelet architecture are described.
The specialized use of the Coderack by the adaptive web
framework's (AWF) Smiley is discussed.
The codelet scheduling mechanism is discussed.
A variety of Smiley extensions to the Coderack are reviewed.
The Coderack infrastructure functions are
included.
Coderack, This page describes the Copycat
Workspace.
The specialized use of the Workspace by the adaptive web
framework's (AWF) Smiley is discussed.
How text and XML are imported into the Smiley Workspace is described.
Telomeric aging of schematic structures is introduced.
The internal data structure used to represent the state of each
workspace object is included.
The Workspace infrastructure functions are
included.
Workspace
and This page describes the Copycat
Slipnet.
The goal of the Slipnet is reviewed.
Smiley's specialized use of the Slipnet is introduced.
The initial Slipnet network used by the 'Merge
Streams' and 'Virtual Robot' agent-based applications is setup in
initchemistry and is included.
The Slipnet infrastructure and initialization functions are
included.
Slipnet define the basis of our
emergent architecture for deploying agents.
Hofstadter and Mitchell's Copycat infrastructure needs
augmentation with This page describes the Smiley
infrastructure that supports the associative binding of schematic strings to codelets
defined in the Meta file
and Slipnet.
The infrastructure supporting the associations is introduced.
The role of Jeff Hawkins neocortical attributes is discussed.
Relevant Slipnet configurations are
included.
The codelets and supporting functions are included.
associative labeling
of the Workspace objects, but is otherwise essentially able to
provide a parallel environment for the codelet based
agents.
The infrastructure also needs to operate in parallel to reflect
the massively parallel biochemical systems. A start is to
support:
- GPU streams within the Copycat infrastructure, and
- Networks of cooperating Copycats.
There seems to be much potential to gain from biologically
inspired computing. But the difficulty of identifying the
operations of highly parallel and adaptive biological systems
and correctly interpreting biological mechanisms has so far
resulted in speculative proposals that over simplify the
aggregate operation of biological systems.
 Politics, Economics & Evolutionary Psychology |
Business Physics Nature and nurture drive the business eco-system Human nature Emerging structure and dynamic forces of adaptation |
 |
integrating quality appropriate for each market |
|