Transcript A-MAZE NEST, Meta-compexity Management

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Applied Mathematics Ability Zone
NEST-IDEA Seminar
"Interdisciplinarity in Research" 22nd, June 2004
A-MAZE
Towards the Identification of
Real-World Meta-Complexity
(ENEA’s contribution)
Adam Maria Gadomski
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
A-MAZE
-
ENEA
Key Concepts
intelligence
REAL-WORLD
technology
COMPLEXITY
computation
A-MAZE
-
ENEA Perspective
Socio-Cognitive Engineering
+ Human Errors
intelligence
REAL-WORLD
technology
Software Safety + Large
Infrastructures Protection
COMPLEXITY
computation
Bio-Informatics + HighPerformance Computing
A-MAZE
-
ENEA perspective
Systemic Real-World Complexity (RWC)
HUMAN
POWER
The pictures from Internet
HUMAN
IGNORANCE
A-MAZE - ENEA contribution:
Towards 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 - ENEA contribution:
Towards the Identification of Real-World Meta-Complexity
Complexity of:
Intervention domain, actions/activities,
methods/methodology, contexts and … subjects
Activity lines
Coordination, Teaching and Research
Activity fields
Intelligence, technology and computation
Activity specific domains ( Testbeds)
C…
. Will be completed yet IN THE NEAR FUTURE.
Interdisciplinary Real-world SocioCognitive Complexity & Its
Management
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
The Materials of : SCEF- 2003 International Workshop 30 Sep., 1 Oct.
2003 , Rome http://erg4146.casaccia.enea.it/SCEF
Human
ZOOM
Complex systems
Made of
many non-identical elements
connected by diverse interactions.
NETWORK
About Intervention Domain: Human Errors
Socio-Cognitive Engineering application for
Multi-grid Large Complex Critical Systems/ Infrastructures (LCCI)
(such as electricity, telecommunication, gas networks)
Human component
Artificial Highly-Autonomous
(Intelligent Agent) component for
Decision-support systems
Production/Transmission
/Control component
of Physical &Technological
Layers
Technological Grid
Copyright: High-Intelligence & Decision Research Group, CAMO, ENEA, http://erg4146.casaccia.enea.it
Organisation
Network
Author: Adam Maria Gadomski, 28/09/2003
About Intervention ACTIVITIES
SCE contributes to the Vulnerability Analysis
Human
Factors
and to the Improvement of Robustness of Large
Complex Critical Systems (Humans-Technology
Systems).
Human
Errors
Key Intervention Activities
Social
Consequences
• 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
Design of System
Modification
(*) For Socio-Cognitive Engineering
System Validation
and Design of
self- regulation
Management
Strategy
see: http://erg4146.casaccia.enea.it/SCEF/index.html
Copyright: High-Intelligence & Decision Research Group, CAMO,ENEA, http://erg4146.casaccia.enea.it
Adam M. Gadomski, 27/09/2003
SOCIO-COGNITIVE ENGINEERING
Integrated Approach
Complexity Domains: Sustainable Development
Strategic Factors (Application of the TOGA Methodology covers here computational
modelling task)
Technology Barrier
Knowledge Barrier
Technology is nothing without Competences
Competences are nothing without MotivationManagement
Cognitive Barrier
Organizational Barrier
Cultural Barrier
Management is inefficient under not adequate
Organizational Constrains.
All above are nothing if Socio-Cultural Context
are neglected.
Copyright: High-Intelligence & Decision Research Group, CAMO, ENEA , http://erg4146.casaccia.enea.it
Adam M. Gadomski, 28/09/2003
SCE: Problem of
Real-word Complexity
Different
Interrelations
Different
Methods
Different Study
Directions
Different
Perspectives
HID
Different
Dependences
Adam Maria Gadomski, http:// erg4146.casaccia.enea.it/
High-Intelligence & Decision Research Group
All in Human-Technology Systems is Complex
Domain
Tools: Conceptualization,Methods, Methodologies
Management
TOOLS
DOMAIN
Complex
Activites
MANAGEMENT
Complex
Complex
Complex Context
HID
Complex
Modeling of SocioCognitive Systems
Adam Maria Gadomski, http:// erg4146.casaccia.enea.it/
High-Intelligence & Decision Research Group
About SCE Complexity
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
HID
Adam Maria Gadomski, http:// erg4146.casaccia.enea.it/
High-Intelligence & Decision Research Group
SOCIO-COGNITIVE ENGINEERING:
Objectives
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
Copyuright: High-Intelligence & Decision Research Group, CAMO, ENEA , http://erg4146.casaccia.enea.it
Adam M. Gadomski, 28/09/2003
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
User & Decision-Maker
Models & Architecture
TOGA
Copyright: High-Intelligence & Decision Research Group, CAMO,ENEA, http://erg4146.casaccia.enea.it
Intelligent
Organisation
Modelling &
Simulation
Adam M. Gadomski, 27/09/2003
About Methodology
How is possible to cope with so complex domain and
objectives?
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:
2
3
Intelligent Agent
1
Environment
Ref. Related to TOGA: http://erg4146.casaccia.enea.it/wwwerg26701/Gad-toga.htm
Copyright High-Intelligence & Decision Research Group, CAMO, ENEA , http://erg4146.casaccia.enea.it
Adam M. Gadomski, 28/09/2003
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.
DG
F
P
carrier relation ( it is opposite to the property
relation)
Cause-consequence relation
Layers: DG - Design-Goals, F – Functions, P – processes, S - systems
S
TOGA: Top-down Intelligent Agent
Decomposition Paradigms, 2a
- Information - How situation looks
- Past/Present/Future states of
Domain-of-Activity (D-o-A)
I
P
K
“ Mind Cell” Elementary
IPK Computational
Model (Information,
Preferences, Knowledge)
- 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-ofActivity (operational knowledge)
Information processing by Knowledge: I’ = K j( I ), j=1, …N, where choice
of j depends from Preferences.
Copyright High-Intelligence & Decision Research Group, CAMO, ENEA , http://erg4146.casaccia.enea.it
Adam M. Gadomski, 28/09/2003
TOGA: Top-down Multi Intelligent
Agent Paradigms, 2b
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.
IA
Interv.
Goal
Tasks
Actions
carrier relation
Intelligent Agent World
En
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.
Copyright High-Intelligence & Decision Research Group, CAMO, ENEA , http://erg4146.casaccia.enea.it
Adam M. Gadomski, 28/09/2003
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].
The top methodology includes in parallel, top-down goal-oriented
tools development and their subsequent applications.
Examples
Copyright High-Intelligence & Decision Research Group, CAMO, ENEA , http://erg4146.casaccia.enea.it
Adam M. Gadomski, 28/09/2003
SCE Ontological Tools -TOGA
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
HID
Adam Maria Gadomski, http:// erg4146.casaccia.enea.it/
High-Intelligence & Decision Research Group
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]
DSS
IDSS
Provides passive Informational Aid and Toolkits
Provides active, partially autonomous Decisional Aid
which involve human-like computational intelligence.
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
Copyright High-Intelligence & Decision Research Group, CAMO, ENEA , http://erg4146.casaccia.enea.it
Adam M. Gadomski, 28/09/2003
INTELLIGENT DECISION SUPPORT FOR RESEARCH MANAGEMENT
EXAMPLE
Research
Activities
Situation Assessment & Decision Making is based on:
Information: DOMAIN status,
Knowledge: rules, procedures, instructions,
Preferences: role criteria, risk criteria, resources criteria,...
Administrative
Activities
Continuous
monitoring
Actions
Financial &
Decisional
Requests/constrains
SIGRE
Periodical
monitoring
Information
INTELLIGENT
DECISION
SUPPORT
SYSTEM
Sc. Tasks
MIND
Strategic Activities
Copyright High-Intelligence & Decision Research Group, CAMO, ENEA , http://erg4146.casaccia.enea.it
link to computer
networks
Adam M. Gadomski, 28/09/2003
Conclusions
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.
HID
Adam Maria Gadomski, http:// erg4146.casaccia.enea.it/
High-Intelligence & Decision Research Group
Conclusions
Anticipatory extrapolations
Future Grow in Arbitrary Units
500
400
Physics & Energy
300
Chemistry & Bioengin.
200
Social & Knowledge
Engin.
100
0
2050
2025
2000
1975
1950
1925
1900
Current name is SocioCognitive Engineering
Extrapolation of the current trends in three basic macro-engineering domains. [US Sources, DARPA,
Web, 2000]
HID
Adam Maria Gadomski, http:// erg4146.casaccia.enea.it/
High-Intelligence & Decision Research Group
For more information see:
References
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.
A.M.Gadomski, Socio-Cognitive Scenarios for Business Intelligence Reinforcement:
TOGA Approach, The paper preliminary accepted for publication in "Cognitive Science“
,Springer V. 2003.
7.
HID
Adam Maria Gadomski, http:// erg4146.casaccia.enea.it/
High-Intelligence & Decision Research Group