Wissensmanagement

Tim Berners-Lee :   –   Design Issues  –  Architectural and philosophical points

–  Notes :

• In the physical sciences the entropy associated with a situation is a measure of the degree of randomness.
The second law of thermodynamics states that entropy always increases in the universe.
High entropy equals high level of chaos.

• The meanings of words, sentences, and texts can change with time cultural and emotional conditions, different sources of knowledge and from community to community.
The consequence of this fact is that a true logical proposition in one relationship can be false in another.

Vámos Tibor (1990): Computer Epistemology. World Scientific.

–  AUTOR:

•  Karl-Erik Sveiby    ( "founding fathers" of Knowledge Management )

•  Consultant & Professor in Knowledge Management

•  Professor (Chair) in Knowledge Management at Hanken Business School, Helsinki, Finland.

–  AUTORS:

•  David Israel

•  John Perry

–  AUTOR:

•   Karl-Erik Sveiby    ( "founding fathers" of Knowledge Management )

•  Consultant & Professor in Knowledge Management

•  Professor of Knowledge Management at the Hanken Business School, Helsinki, Finland.

–  QUOTATION :

KPMG LLP's Chief Knowledge Officer Michael J. Turillo says that:

"knowledge management cannot be done without technology."

Some myths that surround the murky confluence of information technology(IT) and knowledge management(KM).

MYTH:

"Knowledge management technologies deliver the right information to the right person at the right time. "

MYTH:

"Information technologies can store human intelligence and experience."

MYTH:

"Information technologies can distribute human intelligence. "

"The fact of information in a database doesn't ensure that people will see or use the information," Malhotra says.

"Most of our knowledge management technology concentrates on efficiency and creating a consensus-oriented view. The data therein is rational, static and without context."
And such systems, he adds, do not account for renewal of existing knowledge and creation of new knowledge.

–  AUTOR:

•  Carol Hildebrand - email: <cjh@cio.com>

Harry Scarbrough and Jacky Swan
Refereed Paper submitted to the British Academy of Management Conference, ‘Managing Diversity ’, Manchester, 1-3 September, 1999.

–  ABSTRACT :

This paper reviews the emergence of the discourse of Knowledge Management and cites it as a test case of the usefulness and limitations of the ‘ management fashion’ perspective. A literature review of the Knowledge Management and Learning Organization literatures leads to propositions to do with the cyclical and autistic character of the production of management discourse and the correlation between a discursive affiliation to technology and widespread acceptance by managers.

The findings on Knowledge Management correspond to some degree with the classic features of a management fashion - the effects of conceptual ambiguity and the normal curve in interest levels being particular characteristics. However, evidence on the reflexive and professionally-differentiated appropriation of Knowledge Management concepts by the IS and HR communities - and on the adoption of managerial innovations more generally - highlights some of the limitations of the fashion perspective.

We outline an alternative interpretation which emphasises the reflexive and situated appropriation of concepts like KM according to particular organizational contexts.
This alternative view has a number of advantages.
It allows us to explain the disjunctive and enduring effects of management discourses in terms of their path-dependent and ‘disembedding’ appropriation by particular communities.
This helps to account for the discrete nature of management discourses and the lack of learning between one discourse and the next. Reflexive exploitation of such discourses by ‘user’ groups is seen as a more important driver of the fashion cycle than the more opportunistic tactics of knowledge suppliers.

Overall, these points help to locate discourses such as KM in a much wider debate about the changing characteristics of ‘knowledge production’ in contemporary society, and specifically the growing importance of knowledge produced reflexively at its point of application.

–  QUOTATION :

KM (Knowledge Management) is not easy to define and many definitions supplied in the literature are highly ambiguous.

The ambiguity of the concept, however, is itself a clue to the fashion-setting possibililities of this discourse;

ambiguity makes KM amenable to multiple interpretations and remouldings which potentially extend its relevance across different communities of practice.

In this paper, therefore, KM will be defined broadly and inclusively to cover a loosely connected set of ideas, tools and practices centring on the communication and exploitation of knowledge in organizations.

Harry Scarbrough and Jacky Swan  
“ Knowledge Management and the Management Fashion perspective.  ”  Introduction.

–  AUTOR:

•  Harry Scarbrough

•  Leicester University Management Centre,University Rd., Leicester, LE1 7RH, UK.   Email: <harry.scarbrough@wbs.ac.uk>

•  Jacky Swan

•  Warwick Business School ,  IKON ,  The University of Warwick, Coventry, CV4 7AL, UK.   Email: <jacky.swan@wbs.ac.uk>

© Copyright, 1999, Harry Scarbrough, Jacky Swan

–  ABSTRACT :

Although knowledge representation is one of the central and in some ways most familiar concepts in AI, the most fundamental question about it
–  What is it?  – has rarely been answered directly. Numerous papers have lobbied for one or another variety of representation, other papers have argued for various properties a representation should have, while still others have focused on properties that are important to the notion of representation in general.

In this paper we go back to basics to address the question directly.

We believe that the answer can best be understood in terms of five important and distinctly different roles that a representation plays, each of which places different and at times conflicting demands on the properties a representation should have.

We argue that keeping in mind all five of these roles provides a usefully broad perspective that sheds light on some longstanding disputes and can invigorate both research and practice in the field.

–  AUTORS:

•  Randall Davis     MIT AI Lab   Email: <davis@csail.mit.edu>

•  Howard Shrobe   MIT AI Lab and Symbolics, Inc.  Email: <hes@csail.mit.edu>

•  Peter Szolovits     MIT Electrical Engineering and Computer Science, EECS   Email: <psz@mit.edu>

(© MIT  Massachusetts Institute of Technology ).

–  AUTORS:

•  Claude Elwood Shannon (1916 - 2001)  is a research mathematician at the Bell Telephone Laboratories and Donner professor of science
at the Massachusetts Institute of Technology.

•  Warren Weaver (1894 - 1978) a consultant on scientific projects to the Sloan Foundation, has had a distinguished academic, government,
and foundation career.

•  Both authors have received numerous awards and honors.

–  ABSTRACT :

People communicate with each other in sentences that incorporate two kinds of information:
propositions about some subject, and metalevel speech acts that specify how the propositional information is used as an assertion, a command, a question, or a promise.
By means of speech acts, a group of people who have different areas of expertise can cooperate and dynamically reconfigure their social interactions to perform tasks and solve problems that would be difficult or impossible for any single individual.

This paper proposes a framework for intelligent systems that consist of a variety of specialized components together with logic-based languages that can express propositions and speech acts about those propositions.

The result is a system with a dynamically changing architecture that can be reconfigured in various ways:
- by a human knowledge engineer who specifies a script of speech acts that determine how the components interact;
- by a planning component that generates the speech acts to redirect the other components; or
- by a committee of components, which might include human assistants, whose speech acts serve to redirect one another.
The components communicate by sending messages to a Linda-like blackboard, in which components accept messages that are either directed to them or that they consider themselves competent to handle.

–  AUTOR:

•  John F. Sowa Biography

© Copyright 2002, John F. Sowa .

–  PREFACE to Knowledge Representation :

Socrates said he was the midwife to his listeners, i.e., he made them reflect better concerning that which they already knew and become better conscious of it.  If we only knew what we know, namely, in the use of certain words and concepts that are so subtle in application, we would be astonished at the treasures contained in our knowledge.

Immanuel Kant , Vienna Logic.

–  AUTOR:

•  John F. Sowa, Biography

–  ABSTRACT :

As ontologies become common in more applications and as those applications become larger and longer-lived, it is becoming increasingly common for ontologies to be developed in distributed environments by authors with disparate backgrounds.
Ontologies that are expected to be collaboratively created and maintained over time by authors in many locations present special challenges to the problem of conceptual modeling.

In this paper, we will discuss conceptual modeling issues and focus on those topics with elevated importance in distributed environments.

We will draw on our experience creating and maintaining ontologies in differing knowledge representation and reasoning environments over the last decade. Many of our recent observations are drawn from our experiences in the DARPA High Performance Knowledge Base Program.
This program generated dozens of knowledge bases authored by people of varying expertise in both knowledge representation and reasoning as well as domain experience.

Our efforts in merging the ontologies, loading them for coordinated use, and modifying them to meet evolving needs shape much of the material in this paper. Additional sources of observations are from designing and building a number of e-commerce ontologies (with content merged from multiple sources) and also from a few families of description logic applications including the PROSE/QUESTAR family of configurators and the FindUR knowledge-enhanced search applications.

–  AUTOR:

•   Deborah L. McGuinness     Email: <dlm@ksl.stanford.edu>
Associate Director and Senior Research Scientist,
Stanford Computer Science.   Knowledge Systems Laboratory , Gates Building 2A,
Stanford University . 450 Serra Mall, Stanford, California 94305. USA.

© Deborah L. McGuinness. Conceptual Modeling for Distributed Ontology Environments, In the Proceedings of The Eighth International Conference on Conceptual Structures Logical, Linguistic, and Computational Issues (ICCS 2000), Darmstadt, Germany , August 14-18, 2000.

–  ABSTRACT :

The Internet is a giant semiotic system.
It is a massive collection of Peirce's three kinds of signs:
icons, which show the form of something;   indices, which point to something; and   symbols, which represent something according to some convention.

But current proposals for ontologies and metadata have overlooked some of the most important features of signs.
A sign has three aspects: it is

(1)   an entity that represents
(2)  another entity to
(3)   an agent.

By looking only at the signs themselves, some metadata proposals have lost sight of the entities they represent and the agents   –  human, animal, or robot   –  which interpret them. With its three branches of syntax, semantics, and pragmatics, semiotics provides guidelines for organizing and using signs to represent something to someone for some purpose.
Besides representation, semiotics also supports methods for translating patterns of signs intended for one purpose to other patterns intended for different but related purposes.

This article shows how the fundamental semiotic primitives are represented in semantically equivalent notations for logic, including controlled natural languages and various computer languages.

–  AUTOR:

•  John F. Sowa, Biography   <sowa@bestweb.net>

© Copyright, John F. Sowa .

Presented at ICCS'2000 in Darmstadt, Germany, on August 14, 2000. Published in B. Ganter & G. W. Mineau, eds., Conceptual Structures: Logical, Linguistic, and Computational Issues, Lecture Notes in AI #1867, Springer-Verlag, Berlin, 2000, pp. 55-81.

–  PREFACE to Building, Sharing, and Merging Ontologies :

The art of ranking things in genera and species is of no small importance and very much assists our judgment as well as our memory. You know how much it matters in botany, not to mention animals and other substances, or again moral and notional entities as some call them.
Order largely depends on it, and many good authors write in such a way that their whole account could be divided and subdivided according to a procedure related to genera and species. This helps one not merely to retain things, but also to find them.
And those who have laid out all sorts of notions under certain headings or categories have done something very useful.

Gottfried Wilhelm von Leibniz,  “New Essays on Human Understanding  ”

–  ABSTRACT :

For centuries,
•  philosophers have sought universal categories for classifying everything that exists,
•  lexicographers have sought universal terminologies for defining everything that can be said, and
•  librarians have sought universal headings for storing and retrieving everything that has been written.

During the 1970s, the ANSI SPARC committee proposed the three-schema architecture for defining and integrating the database systems that manage the world economy.

Today, the semantic web has enlarged the task to the level of

• classifying,   • labeling,   • defining,   • finding,   • integrating, and  • using everything on the World Wide Web,

which is rapidly becoming the universal repository for all the accumulated knowledge, information, data, and garbage of humankind.

This talk surveys the issues involved, the approaches that have been successfully applied to small systems, and the ongoing efforts to extend them to distributed, interconnected, rapidly growing, heterogeneous systems.

–  AUTOR:

•   John F. Sowa Biography   <sowa@bestweb.net>

© Copyright, John F. Sowa .

–  ABSTRACT :

The World Wide Web is an information resource with virtually unlimited potential.
However, this potential is relatively untapped because it is difficult for machines to process and integrate this information meaningfully.
Recently, researchers have begun to explore the potential of associating web content with explicit meaning, in order to create a Semantic Web. Rather than rely on natural language processing to extract this meaning from existing documents, this approach requires authors to describe documents using a knowledge representation language.

Although knowledge representation can solve many of the Web's problems, existing research cannot be directly applied to the Semantic Web. Unlike most traditional knowledge bases, the Web is highly decentralized, changes rapidly, and contains a staggering amount of information.

This thesis examines how knowledge representation must change to accommodate these factors.

It presents a new method for integrating web data sources based on ontologies, where the sources explicitly commit to one or more autonomously developed ontologies. In addition to specifying the semantics of a set of terms, the ontologies can extend or revise one another.

This technique permits automatic integration of sources that commit to ontologies with a common descendant, and when appropriate, of sources that commit to different versions of the same ontology.

The potential of the Semantic Web is demonstrated using SHOE, a prototype ontology language for the Web. SHOE is used to develop extensible shared ontologies and create assertions that commit to particular ontologies. SHOE can be reduced to datalog, allowing it to scale to the extent allowed by the optimized algorithms developed for deductive databases. To demonstrate the feasibility of the SHOE approach, we describe a basic architecture for a SHOE system and a suite of general purpose tools that allow SHOE to be created, discovered, and queried. Additionally, we examine the potential uses and difficulties associated with the SHOE approach by applying it to two problems in different domains.

–  AUTOR:

•  Jeffrey Douglas Heflin, Doctor of Philosophy,   Publication.

•  Dissertation directed by : Professor James A. Hendler ,   Department of Computer Science ,   University of Maryland.

© Reformatted - PDF (928K)

Yogesh Malhotra, Ph.D.
In K. Srikantaiah & M.E.D. Koenig (Eds.), Knowledge Management for the Information Professional. Medford, N.J.: Information Today Inc., pp. 37-.

–  ABSTRACT :

Most extant knowledge management systems are constrained by their overly rational, static and acontextual view of knowledge. Effectiveness of such systems is constrained by the rapid and discontinuous change that characterizes new organizational environments.

The prevailing knowledge management paradigm limits itself by its emphasis on convergence and consensus-oriented processing of information.

Strategy experts have underscored that the focus of organizational knowledge management should shift from ‘prediction of future’ [that cannot be computed] to ‘anticipation of surprise.’

Such systems may be enabled by leveraging the divergent interpretations of information based upon the meaning-making capability of human beings.

By underscoring the need for synergy between innovation and creativity of humans and the advanced capabilities of new information technologies, this article advances current thinking about knowledge management.

–  QUOTATION :

"To conceive of knowledge as a collection of information seems to rob the concept of all of its life...

Knowledge resides in the user and not in the collection.

It is how the user reacts to a collection of information that matters."

Churchman, C.W.  “ The Design of Inquaring Systems ”   Basic Books, New York, NY 1971.

–  MOTTO :

A Constructivist Corollary :

“ There is Nothing So Practical as Good Practice of Theory ”.

Yogesh Malhotra

–  AUTOR:

•  Yogesh Malhotra, Ph.D

•  Ph.D. in MIS, Management Controls & Quantitative Methods University of Pittsburgh Katz Graduate School of Business

•  Résumé, Biography

© Copyright, 2000, Yogesh Malhotra, Ph.D.

- Computer Science Department
- Stanford University

Sponsored by the :
- Defense Advanced Research Projects Agency
- Informations Systems Office

HPKB Program :
High-Performance Knowledge Bases (HPKB) Program

–   ABSTRACT :

We are developing technology that will support :

collaborative construction and effective use of
distributed large-scale repositories of
highly expressive reusable ontologies

–   INNOVATIVE CLAIMS :

We will develop representation, reasoning, and user interface technology that will support collaborative construction and effective usage of distributed large-scale repositories of highly expressive reusable ontologies

We will build on the results of the DARPA Knowledge Sharing Effort, specifically by using the

Knowledge Interchange Format (KIF)

as a core representation language and the Ontolingua system as a core ontology development environment.

–  TECHNICAL RATIONALE  :

We are developing technology that will enable construction and effective usage of distributed large-scale repositories of highly expressive reusable ontologies.

We consider ontologies to be domain theories that specify a domain-specific vocabulary of entities, classes, properties, predicates, and functions, and a set of relationships that necessarily hold among those vocabulary items.

Ontologies provide a vocabulary for representing knowledge about a domain and
for describing specific situations in a domain.

They can be used as building block components of knowledge bases, object schema for object-oriented systems, conceptual schema for data bases, structured glossaries for human collaborations, vocabularies for communication between agents, class definitions for conventional software system, etc.

–  AUTORS:

•   Richard Fikes;    Co-Principal Investigator ;   Co-Scientific Director, Knowledge Systems Laboratory;    <fikes@ksl.stanford.edu>

•   Daphne Koller;   Co-Principal Investigator ;   Robotics Laboratory;   <koller@cs.stanford.edu>

–  ABSTRACT :

Knowledge Engineering was in the past primarily concerned with building and developing knowledge-based systems, an objective which puts Knowledge Engineering in a niche of the world-wide research efforts - at best.

This has changed dramatically:

Knowledge Engineering is now a key technology in the upcoming knowledge society.

Companies are recognizing knowledge as their key assets, which have to be exploited and protected in a fast changing, global and competitive economy.

This situation has led to the application of Knowledge Engineering techniques in Knowledge Management.

The demand for more efficient (business to) business processes requires the interconnection and interoperation of different information systems.

But information access and integration is not an algorithmic task that is easy to solve:

much knowledge is required to resolve the semantic differences of data residing in two information systems.

Thus Knowledge Engineering has become a major technique for information integration.

And, last but not least the fast growing World Wide Web generates an ever-increasing demand for more efficient knowledge exploitation and creation techniques.

Here again Knowledge Engineering technologies may become the key technology for solving the problem.

In this paper we discuss these recent developments and describe our view of the future.

–  AUTORS:

•  Rudi Studer;    Institute AIFB, University of Karlsruhe  <studer@aifb.uni-karlsruhe.de>

•  Steffen Staab,    Institute AIFB, University of Karlsruhe ;   <staab@aifb.uni-karlsruhe.de>

•  Stefan Decker ,   Stanford University, CA, USA.  <Stefan.Decke@DERI.org>

•  Dieter Fensel ,   Division of Mathematics & Computer Science, Vrije Universiteit Amsterdam , Addresses: www.sti2.org   www.sti-innsbruck.at

© Springer-Verlag Berlin Heidelberg 1999

–  ABSTRACT :

Conceptual Graphs and Formal Concept Analysis have in common basis concerns:

the focus of conceptual structures, the use of diagrams for supporting communication,
the orientation by Peirce's Pragmatism, and the aim of representing and processing KNOWLEDGE.

These concerns open rich possibilities of interplay and integration.

We discuss the philosophical foundations of both disciplines, and analyze their specific qualities. Based on this analysis, we discuss some possible approaches of interplay and integration

–  AUTORS:

•  Guy Mineau;    <mineau@ift.ulaval.ca>

•  Gerd Stumme;   <stumme@mathematik.tu-darmstadt.de>

•  Rudolf Wille;   <wille@mathematik.tu-darmstadt.de>

–  ABSTRACT :

This article describes a first synthesis of a Conceptual Graph and RDF(S) approach for representing and querying document contents.

The framework of this work is the ESCRIRE project the main goal of which is to compare three
KNOWLEDGE REPRESENTATION formalisms (KR):
- conceptual graphs (CG),
- descriptions logics (DL), and
- object-oriented representation languages (OOR)

for querying about document contents by relying on ontology-based annotations on document content.

This comparison relies on an expressive XML-based pivot language to define the ontology and to represent annotations and queries;

it consists of evaluating the capacity of the three KR formalisms for
expressing the features of the pivot language.

Each feature of the pivot language is translated into each KR formalism, which is than used to draw inferences and to answer queries. Our team was responsible on the CG part.

The motivation of this paper is to give a first synthesis of the translation process from the pivot language to RDF(S) and CG, to underline the main problems encountered during this translation.

–  KEYWORDS:

•  Knowledge representation, Conceptual Graphs, Ontologies, RDFS, XML, and Semantic information retrieval.

–  AUTOR:

•  R. Carolina Medina Ramírez;   <cmedina@sophia.inria.fr>

•  Olivier Corby;   <corby@sophia.inria.fr>

•  Rose Dieng-Kuntz;   <dieng@sophia.inria.fr>

–  CONCEPTUAL GRAPHS (CGs) :

Conceptual graphs (CGs) are a system of logic based on
the existential graphs of Charles Sanders Peirce and
the semantic networks of artificial intelligence.

They express meaning in a form that is logically precise,
humanly readable, and computationally tractable.

With their direct mapping to language, conceptual graphs serve as an intermediate language for translating computer-oriented formalisms to and from natural languages.

With their graphic representation, they serve as a readable,
but formal design and specification language.

CGs have been implemented in a variety of projects for information retrieval, database design, expert systems, and natural language processing.

A World of Conceptual Graphs

–  CONCEPTUAL MODELING :

Conceptual modeling is about clear, unambiguous,
declarative description of object semantics and relationships.

22nd International Conference on Conceptual Modeling

CONCEPTUAL MODELING is the description of INFORMATION SYSTEMS
on the meta-level, where conceptual processes, model constructions and knowledge representations play an essential role.

Journal of Conceptual Modeling January 2002 Issue: 23  –  "Peircean" Reorganization in Conceptual Modeling Terminology

In practice, according to Kangassalo (1992), conceptual modeling, in short, is:

"a process of forming and collecting conceptual knowledge about the Universe of Discourse (UoD) and documenting the results in the form of a conceptual schema"

CONCEPTUAL MODELING is a methodology for constructing conceptual schemata.

–  ABSTRACT :

This article presents CGWorld a Web based workbench for joint distributed development of a knowledge base of conceptual graphs, which resides on a central server.

It is implemented in Java and Prolog.

The workbench includes a graphical, easy to use CG Editor written as a Java Applet.

CGWorld has facilities for translating CGs between four different formats - Display form, Internal Prolog Representation, First Order Predicate Calculus, and CGIF, and textual and graphical browsing features for easy search on KBs of conceptual graphs.

Also, using the Application Server technology, Internet access is added to previously developed CG applications. Using the standard Internet client - the browser, it is possible to add new features allowed by the new presentation layer.

–  MOTIVATION :

In summary, the goals that had to be met by the CGWorld workbench have been:

•  to allow for collaborative, distributed acquisition and editing of a CG knowledge base;

•  to provide easy search and navigation in a large KB (Knowledge Base );

•  to maintain different representation languages, thus accommodating the needs of different users of CGWorld and the different applications the KB of CGs is used in;

•  easy to use by non-expert in CG theory users graphical editor and viewer for CGs(Conceptual Graph);

•  integration and addition of Web access to currently or previously developed CG applications, written in different programming languages.

–  AUTORS :

•  Pavlin Dobrev   ProSyst Bulgaria Ltd., Sofia, Bulgaria.   <p_dobrev@prosyst.com>

•  Kristina Toutanova   Stanford University, CA, USA.   <kristina@cs.stanford.edu>

•  Kristina Toutanova currently researcher in the NLP group at Microsoft Research.

–  ABSTRACT :

This article summarizes the authors’ experience in implementing CGWorld - a web-based workbench for distributed development of a knowledge base of conceptual graphs, stored on a central server.

The conceptual graph theory is discussed and the implementation of it in CGWorld is presented.

–  AUTORS :

•  Pavlin Dobrev   ProSyst Bulgaria Ltd., Sofia, Bulgaria.   <pavlin@prosyst.com>

•  Albena Strupchanska   Linguistic Modelling Department (LMD),   Institute for Parallel Processing (IPP),   Bulgarian Academy of Sciences (BAS),
   Sofia, Bulgaria.   <albena@lml.bas.bg>

•  Kristina Toutanova    <kristina@cs.stanford.edu>   Stanford University, CA, USA.

•  Kristina Toutanova currently researcher in the NLP group at Microsoft Research.

–  DEFINITION :

Selbstorganization :

Als Selbstorganisation wird in der Systemtheorie hauptsächlich eine
Form der Systementwicklung bezeichnet, bei der die formgebenden, gestaltenden und beschränkenden Einflüsse von den Elementen
des sich organisierenden Systems selbst ausgehen.

From Wikipedia, the free encyclopedia  Selbstorganization

Self-organization :

Self-organization is a process of attraction and repulsion in which
the internal organization of a system, normally an open system, increases in complexity
without being guided or managed by an outside source.
Self-organizing systems typically (but not always) display emergent properties.

From Wikipedia, the free encyclopedia  Self-organization

Self-organization :

Self-organization is a process where the organization (constraint, redundancy) of a system spontaneously increases, i.e. without this increase being controlled by the environment
or an encompassing or otherwise external system

From Principia Cybernetica Web  Self-organization

LUIS M. ROCHA

- Complex Systems Modeling

- Modeling, Algorithms, and Informatics Group (CCS-3)

- Los Alamos National Laboratory, MS B256

- Los Alamos, New Mexico 87545, USA

–  ABSTRACT :

In this paper I sketch a rough taxonomy of self-organization which may be of relevance in the study of cognitive and biological systems.

I frame the problem both in terms of the language of second- order cybernetics as well as the language of current theories of self-organization and complexity.

The goal of establishing such a taxonomy is to allow for a classification of different tools used both in Artificial Intelligence and Artificial Life, so that different aspects of cognitive and biological systems may be incorporated in more accurate models of such systems.

In particular, I defend, on the one hand, that self-organization alone is not rich enough for our intended simulations, and on the other, that genetic selection in biology and symbolic representation in cognitive science alone leave out the very important (self-organizing) characteristics of particular embodiments of evolving and learning systems.

–  KEYWORDS :

Self-organization, Semantic Closure, Semiotics, Emergence, Evolutionary Strategies, Artificial Life, Artificial Intelligence.

–  AUTOR:

•  LUIS M. ROCHA;    <rocha@lanl.gov>  or   <rocha@santafe.edu>

–  ABOUT KnowledgeBOARD :

KnowledgeBoard started life as a European Commission-funded Special Support Action within the IST FP6 framework.

Now run by Sift Media as a self-moderating global community, KnowledgeBoard has over 25,000 members and is home to the world's leading thinkers in corporate and academic knowledge.
Experts can collaborate on subjects of innovation and knowledge management, as well as having access to news, features and white papers covering the latest topics in the knowledge management arena. 

International experts from industry and academia will trigger discussions and lead the debate about innovation and knowledge management by hosting online keynote presentations, Q&A sessions, offline workshops and giving expert interviews.

Various case studies and cutting edge material about different knowledge related aspects of innovation and knowledge management will be a backbone for all discussions and activities.
In addition, EC research projects will take the opportunity to present their latest findings.

–  EDITOR:

•  Louise Druce   <editor@knowledgeboard.com>