a-maze nest-idea seminar "interdisciplinarity in research" 22nd, june 2004 applied...

A-MAZEA-MAZE

NEST-IDEA Seminar

"Interdisciplinarity in Research" 22nd, June 2004

Applied Mathematics Ability Zone

Adam Maria Gadomski

(ENEA’s contribution)

Towards the Identification of Towards the Identification of

Real-World Meta-ComplexityReal-World Meta-Complexity

http://www.nest-idea.kpk.gov.pl/filelist.html

About NEW RESEARCH INITIATIVE:

META-COMPLEXITY MANAGEMENT

frameworks

Prepared by : Adam Maria Gadomski, ENEA

Contact person : Adam Maria Gadomski

Email address : [email protected] Phone :

WWW page : http://erg4146.casaccia.enea.it/HID/HID-researchers.htm

Country : ITALY City : Rome

Disciplines : Socio-Cognitive Engineering, System Science

Copyright: High-Intelligence & Decision Research Group, CAMO, ENEA, http://erg4146.casaccia.enea.it Author: Adam Maria Gadomski, 28/09/2003

http://erg4146.casaccia.enea.it/

A-MAZE A-MAZE - - ENEAENEA

REAL-WORLD COMPLEXITY

intelligence

computation technology

Key Concepts

A-MAZE A-MAZE - - ENEA PerspectiveENEA Perspective

REAL-WORLD COMPLEXITY

intelligence

computation technology

Socio-Cognitive Engineering + Human Errors

Software Safety + Large Infrastructures Protection

Bio-Informatics + High-Performance Computing

A-MAZE A-MAZE - - ENEA perspectiveENEA perspective

The pictures from Internet

HUMAN POWER

HUMAN IGNORANCE

Systemic Real-World Complexity (RWC)

A-MAZE A-MAZE - - ENEA contribution:ENEA contribution:

Towards the Identification of Real-World Meta-ComplexityTowards the Identification of Real-World Meta-Complexity

Working Hypothesis

The nature of the complexity is abstract and independent on its physical carriers, but it is closely related to the properties of mathematical tools and their users.

Meta-complexity is focused/based on an abstract intelligence (an abstract intelligent agent), its/his/her : perception, interpretation, inferencing and acting capacities, as well as i/h/h objectives and values.

In this sense

Meta-complexity study is based on human capacities of identification and computational formalization of ontology and epistemology of complexity.

A-MAZE A-MAZE - - ENEA contribution:ENEA contribution: Towards the Identification of Real-World Meta-ComplexityTowards the Identification of Real-World Meta-Complexity

Activity lines

Coordination, Teaching and Research

Complexity of:

Intervention domain, actions/activities, methods/methodology, contexts and … subjects

Activity fields

Intelligence, technology and computation

Activity specific domains ( Testbeds)

C… . Will be completed yet IN THE NEAR FUTURE.

The Materials of : SCEF- 2003 International Workshop 30 Sep., 1 Oct. 2003 , Rome http://erg4146.casaccia.enea.it/SCEF

Selected transparent sheets from:

“Socio-Cognitive Engineering Foundations and Applications: from Humans to Nations (an introduction)”

Adam Maria Gadomski

High-Intelligence & Decision Research Group, CAMO, ENEA

& Sc. Board of ECONA, Italy

Interdisciplinary Real-world Socio-Cognitive Complexity & Its

Management

Complex systems

Made of many non-identical elements

connected by diverse interactions.

NETWORK

Human ZOOM

About Intervention Domain: Human Errors Socio-Cognitive Engineering application for

Multi-grid Large Complex Critical Systems/ Infrastructures (LCCI)

(such as electricity, telecommunication, gas networks)

Copyright: High-Intelligence & Decision Research Group, CAMO, ENEA, http://erg4146.casaccia.enea.it Author: Adam Maria Gadomski, 28/09/2003

Technological Grid

Human Errors

Organisation Network

Human component

Production/Transmission /Control componentof Physical &Technological Layers

Artificial Highly-Autonomous (Intelligent Agent) component for

Decision-support systems


Human Factors

Human Errors

Social Consequences

About Intervention ACTIVITIES

SCE contributes to the Vulnerability Analysis and to the Improvement of Robustness of Large Complex Critical Systems (Humans-Technology Systems).

Key Intervention Activities• Users/human Modelling and Simulation

• Organization Structures and Decision-Making Modelling and Simulation

• Assessment of Social Risk and Impacts

• Intrusions and Mismanagement

Development and Simulation of

Autonomous Artificial Intelligent Organizations embedded in Complex Human-Technology Systems.

Copyright: High-Intelligence & Decision Research Group, CAMO,ENEA, http://erg4146.casaccia.enea.it Adam M. Gadomski, 28/09/2003


About Strategy of Socio-Cognitive Engineering

Socio-Cognitive Engineering (*) takes under consideration the interests and points of view of:

citizens, employers, managers, owners & politicians

SCE Integrated Strategy is human-centered and technology-based

Identification of the System of Interest and

its contexts

System Validation and Design of self-

regulation Management

Strategy


Design of System Modification

(*) For Socio-Cognitive Engineering see: http://erg4146.casaccia.enea.it/SCEF/index.html


SOCIO-COGNITIVE ENGINEERING Integrated Approach

Copyright: High-Intelligence & Decision Research Group, CAMO, ENEA , http://erg4146.casaccia.enea.it Adam M. Gadomski, 28/09/2003

Organizational Barrier

Technology Barrier

Knowledge Barrier

Cognitive Barrier

Cultural Barrier

Technology is nothing without Competences

Competences are nothing without Motivation- Management

Management is inefficient under not adequate Organizational Constrains.

All above are nothing if Socio-Cultural Context are neglected.

Complexity Domains: Sustainable Development Strategic Factors (Application of the TOGA Methodology covers here computational

modelling task)


SCE: Problem of Real-word Complexity

Adam Maria Gadomski, http:// erg4146.casaccia.enea.it/

High-Intelligence & Decision Research Group

HID

Different Interrelations Different

Methods

Different Perspectives

Different Study Directions

Different Dependences

All in Human-Technology Systems is Complex



HID

Domain Tools: Conceptualization,Methods, Methodologies Management

Complex Activites

Complex Context

Complex

Modeling of Socio-Cognitive Systems

DOMAIN

Complex

Complex

TOOLS

MANAGEMENT

About SCE Complexity



HID

Complexity in SCE is not only a physical complexity but it includes complexity of mental processes and actions of an intelligent entity.

SCE complexity includes new attributes, such as :

Vagueness, Uncertainty Conflicts, Incomplete knowledge, Variable access to information, Emotions, Irrationality, Ethical preferences, Organizational & Socio-cultural factors.

All of them influence Decisional Processes

SOCIO-COGNITIVE ENGINEERING: Objectives

Copyuright: High-Intelligence & Decision Research Group, CAMO, ENEA , http://erg4146.casaccia.enea.it Adam M. Gadomski, 28/09/2003

Numerous improvements of real Socio-Cognitive Systems (SCS)

on the levels of efficacy of and interactions between their components ( defined before).

Examples of problems:

- Interaction between individuals and always more complex information and business society,

- Efficiency and “life cycle” of human organizations,

- Relation between decision-making and organization structures

- Diagnosis of pathologies of human organizations

- Individual Interest and Organization Interest impacts

- Strategies of the development: democratic, centralized

- Technological Support and Intelligent Artifacts


SOCIO-COGNITIVE ENGINEERING for LCCIs (Large Complex Critical Infrastructures)

Socio-Cognitive Engineering takes under consideration the interests and points of view of owners, operators and customers of LCCIs :

+ LCCIs customers need the reliability and continuous providing of the services as long as possible and at low cost as possible.

+ LCCIs operators wish to be well informed about the infrastructure state and require its efficient management to satisfy customers expectations + LCCIs owners are focused on the socio-economic aspects of LCCIs.

ENEA’s Competences

Modelling Metodology

TOGATOGA

User & Decision-Maker Models & Architecture

Intelligent Organisation Modelling & Simulation



About Methodology

Top-down Object-Based Goal-oriented Approach (TOGA)

TOGA is goal-oriented complex-knowledge ordering computational tool.

It assumes the top-down observation metaphor, to see complex problems from a bird eye’s view; this means to first identify a problem’s most general context constraints which remain always true and mandatory for every successive level of its specification (“fleshing out”).

It is based on formal step-by-step decomposition of the concepts:

Intelligent Agent Environment

Copyright High-Intelligence & Decision Research Group, CAMO, ENEA , http://erg4146.casaccia.enea.it Adam M. Gadomski, 28/09/2003

How is possible to cope with so complex domain and objectives?

Ref. Related to TOGA: http://erg4146.casaccia.enea.it/wwwerg26701/Gad-toga.htm

12 3


TOGA: Top-down Environment Decomposition Paradigms, 1

Representation of a system in terms of the relation (System,

its Design-Goal). It is formally decomposed into four layers.

F PDG S

carrier relation ( it is opposite to the property relation)Cause-consequence relation

Layers: DG - Design-Goals, F – Functions, P – processes, S - systems

TOGA: Top-down Intelligent Agent Decomposition Paradigms, 2a

- Information -

- How situation looks - Past/Present/Future states of Domain-of-Activity (D-o-A)

- Preferences - - A partial ordering of possible states of D-o-A and they determine what is more important

- Knowledge - - What agent is able to associate (descriptive/model knowledge: rules, models) - What agent is able to do in Domain-of- Activity (operational knowledge)

Information processing by Knowledge: I’ = K j( I ), j=1, …N, where choice

of j depends from Preferences.

I

KP

“ Mind Cell” Elementary IPK Computational

Model (Information, Preferences, Knowledge)



TOGA: Top-down Multi Intelligent Agent Paradigms, 2b

Universal Management Paradigm (UMP)


High-Intelligence & Decision Research GroupHID

Pattern-based Structure: Subjective, Incremental, Recursive

MANAGERMANAGER

INFORMER EXECUTOR

information tasks

ADVISOR

expertises COOPERATINGMANAGER

cooperation

SUPERVISOR

tasks information

Knowledge Preferences

UMP includes 6 canonical roles and their interrelations

TOGA: Interrelation between IA and its World Paradigm, 3

In order to formally understand interactions between designed/identified system and its intelligent designer/researcher it is necessary to pass from the SPG conceptualization of intelligent system functions, to a conceptualization of interventions/actions of an intelligent agent.

For this purpose we need yet to use the WAG (Warld-Action-Goal) approach.

WAG is a representation of the relation between Intelligent Agent World and agents’ Intervention-Goal.

Interv.Goal Tasks Actions

IA

Encarrier relation

Intelligent Agent World


Remarks: All introduced concepts are also representable formally in a declarative manner, as Abstract Objects, i.e. by identificators and attributes list, ie.in the form of data bases.


SCE has to use new thinking methods

TOGA METHODS

The methods are divided on:

1. New Methodology/method of the Cooperation between SCE project partners

2. New Methodology/method for Objectives Achieving,

where the Cooperation Method is focused only on the efficacy of the realization of Objectives Achieving Methodology.

They both, in different proportions, are based on parallel, top-down and goal-oriented application of main paradigms of physics, systemics, cognitive and social sciences related to a generic intelligence. The meta-theoretical approach TOGA is assumed as a initial methodological and ontological framework. [ see References].

Examples

The top methodology includes in parallel, top-down goal-oriented tools development and their subsequent applications.



SCE Ontological Tools -TOGA



HID

TOGA provides tools which can be used for Identification/Specification of real-world problems:

Complex domain: SPG Modelling framework

Complex interventions: WAG Modelling framework

Risky decisions: Risk-based Reasoning Model

Intelligent entity modelling with Human Factors, such as:

Emotions

Irrationalities

Motivations

Fractal-like Multi- and Meta-Modelling,

and Simulations tools are required.

Technology support: IDSS

IDSS: Intelligent Decision Support Systems


What is it ? “Software program that integrates human intellectual and computer capacities

to improve decision making quality, in semi-structured problems situations” [Keen, Scott-Morton, 1996]

Provides active, partially autonomous Decisional Aid which involve human-like computational intelligence.

Provides passive Informational Aid and Toolkits

IDSSIDSS

DSSDSS

When IDSS is important?

• amount of information necessary for the management is so large, or their flow is so intensive, that the probability of human errors under time constrains is not negligible.

• coping with unexpected situation requires remembering, mental elaboration and immediate application of complex professional knowledge, which if not properly used, causes fault decisions.

More information: http://erg4146.casaccia.enea.it/eme-idss0.htm


INTELLIGENT DECISION SUPPORT FOR RESEARCH MANAGEMENT


Situation Assessment & Decision Making is based on:Information: DOMAIN status, Knowledge: rules, procedures, instructions,Preferences: role criteria, risk criteria, resources criteria,...

INTELLIGENTDECISIONSUPPORTSYSTEM

SIGRE

link to computer networks

Periodicalmonitoring

MIND

Sc. Tasks

Continuousmonitoring

Financial &DecisionalRequests/constrains

Research Activities

Actions

Strategic Activities

Administrative Activities

Information

EXAMPLE


Conclusions



HID

Nowadays SCE is a response on dramatically grown risk of negative consequences of Human Errors, it is inevitable tool of XXI Century.

- Complexity of problems requires new 3rd Generation Approaches, such as TOGA multi-factor problem representation and parallel modelling, and IDSS development.

- Key problems refer to the understanding and transparency of decision-making processes for their intelligent actors-contributors.

- Socio-Cognitive Engineering requires new specialists on organization, national and international levels.

- EU promotes assessment of possible socio-cognitive impacts, innovation governance and new updated roles for policymakers.

- EC coordinates cross-integrations of national initiatives with objective of parallel harmonic and sustainable development of science, technology and society.

The above mentioned tasks have to be supported by theoretical foundations and in consequence, by conscious, wise and socio-ethical responsible decision-making.

Conclusions



HID

Anticipatory extrapolations

Extrapolation of the current trends in three basic macro-engineering domains. [US Sources, DARPA, Web, 2000]

0

100

200

300

400

500

19

00

19

25

19

50

19

75

20

00

20

25

20

50

Physics & Energy

Chemistry & Bioengin.

Social & KnowledgeEngin.

Future Grow in Arbitrary Units

Current name is Socio-Cognitive Engineering

References



HID

1 A.M. Gadomski , Lectures on Safety and Reliability of Human-Machine Systems. Materials of SA-EUNET EU Project, 1998. http://tisgi.casaccia.enea.it/projects/isaeunet/manmachine/ppframe.htm

2 A.M. Gadomski , SOPHOCLES Project – Cyber Virtual Enterprise for Complex Systems Engineering: Cognitive Intelligent Interactions Manager for Advanced e-Design, Transparent-sheets, 28/08/2001, ENEA. ITEA. http://erg4146.casaccia.enea.it/SOPHOCLES/

3 A.M.Gadomski. TOGA: A Methodological and Conceptual Pattern for modeling of Abstract Intelligent Agent.Proceedings of the "First International Round-Table on Abstract Intelligent Agent". A.M. Gadomski (editor), 25-27 Gen., Rome, 1993, Publisher ENEA, Feb.1994. http://erg4146.casaccia.enea.it/wwwerg26701/Gad-toga.htm

4 A.M.Gadomski, "The Nature of Intelligent Decision Support Systems". The key paper of the Workshop on "Intelligent Decision Support Systems for Emergency Management ", Halden, 20th-21st October, 1997. http://tisgi.casaccia.enea.it/activities/emergency/eme-idss/

5 A.M.Gadomski, S. Bologna, G.Di Costanzo, A.Perini, M. Schaerf. Towards Intelligent Decision Support Systems for Emergency Managers: The IDA Approach. International Journal of Risk Assessment and Management, 2001.

6 A.M.Gadomski, A.Straszak. Socio-Cognitive Engineering Paradigms for Business Intelligence Modelling: the TOGA conceptualization. Proceedings of the 5th Business

Information System International Conference– BIS 2002, Poznan, Poland, April 24-25, 2002.7. A.M.Gadomski, Socio-Cognitive Scenarios for Business Intelligence Reinforcement:

TOGA Approach, The paper preliminary accepted for publication in "Cognitive Science“ ,Springer V. 2003.

For more information see:

http://erg4146.casaccia.enea.it/wwwerg26701/Gad-toga.htm

a-maze nest-idea seminar "interdisciplinarity in research" 22nd, june 2004 applied...

Documents

research complexity

rome http

management slide

maze enea contribution

epistemology of complexity

network human zoom slide

abstract intelligence

strategy of socio