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A-MAZE NEST-IDEA Seminar "Interdisciplinarity in Research" 22nd, June 2004 Applied Mathematics Ability Zone Adam Maria Gadomski (ENEAs contribution ) Towards.

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Presentation on theme: "A-MAZE NEST-IDEA Seminar "Interdisciplinarity in Research" 22nd, June 2004 Applied Mathematics Ability Zone Adam Maria Gadomski (ENEAs contribution ) Towards."— Presentation transcript:

1 A-MAZE NEST-IDEA Seminar "Interdisciplinarity in Research" 22nd, June 2004 Applied Mathematics Ability Zone Adam Maria Gadomski (ENEAs contribution ) Towards the Identification of Real-World Meta-Complexity

2 About NEW RESEARCH INITIATIVE: META-COMPLEXITY MANAGEMENT frameworks Prepared by : Adam Maria Gadomski, ENEA Contact person : Adam Maria Gadomski address : Phone : WWW page : Country : ITALY City : Rome Disciplines : Socio-Cognitive Engineering, System Science Copyright: High-Intelligence & Decision Research Group, CAMO, ENEA, Author: Adam Maria Gadomski, 28/09/2003http://erg4146.casaccia.enea.it

3 A-MAZE - ENEA REAL-WORLD COMPLEXITY intelligence computation technology Key Concepts

4 A-MAZE - ENEA Perspective REAL-WORLD COMPLEXITY intelligence computation technology Socio-Cognitive Engineering + Human Errors Software Safety + Large Infrastructures Protection Bio-Informatics + High- Performance Computing

5 A-MAZE - ENEA perspective The pictures from Internet HUMAN POWER HUMAN IGNORANCE Systemic Real-World Complexity (RWC)

6 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.

7 A-MAZE - ENEA contribution: Towards 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.

8 The Materials of : SCEF International Workshop 30 Sep., 1 Oct. 2003, Rome 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

9 Complex systems Made of many non-identical elements connected by diverse interactions. NETWORK Human ZOOM

10 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, Author: Adam Maria Gadomski, 28/09/2003http://erg4146.casaccia.enea.it Technological Grid Human Errors Organisation Network Human component Production/Transmission /Control component of Physical &Technological Layers Artificial Highly-Autonomous (Intelligent Agent) component for Decision-support systems

11 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, Adam M. Gadomski, 28/09/2003http://erg4146.casaccia.enea.it

12 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 Copyright: High-Intelligence & Decision Research Group, CAMO,ENEA, Adam M. Gadomski, 27/09/2003http://erg4146.casaccia.enea.it Design of System Modification (*) For Socio-Cognitive Engineering see:

13 SOCIO-COGNITIVE ENGINEERING Integrated Approach Copyright: High-Intelligence & Decision Research Group, CAMO, ENEA, Adam M. Gadomski, 28/09/2003http://erg4146.casaccia.enea.it 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)

14 SCE: Problem of Real-word Complexity Adam Maria Gadomski, erg4146.casaccia.enea.it/ High-Intelligence & Decision Research Group HID Different Interrelations Different Methods Different Perspectives Different Study Directions Different Dependences

15 All in Human-Technology Systems is Complex Adam Maria Gadomski, erg4146.casaccia.enea.it/ High-Intelligence & Decision Research Group HID Domain Tools: Conceptualization,Methods, Methodologies ManagementComplex Activites Complex Context Complex Modeling of Socio- Cognitive Systems DOMAIN Complex TOOLS MANAGEMENT

16 About SCE Complexity Adam Maria Gadomski, erg4146.casaccia.enea.it/ High-Intelligence & Decision Research Group 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

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

18 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. ENEAs Competences Modelling MetodologyTOGA User & Decision-Maker Models & Architecture Intelligent Organisation Modelling & Simulation Copyright: High-Intelligence & Decision Research Group, CAMO,ENEA, Adam M. Gadomski, 27/09/2003http://erg4146.casaccia.enea.it

19 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 eyes view; this means to first identify a problems 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, Adam M. Gadomski, 28/09/2003http://erg4146.casaccia.enea.it How is possible to cope with so complex domain and objectives? Ref. Related to TOGA: 12 3

20 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. FPDGS carrier relation ( it is opposite to the property relation) Cause-consequence relation Layers: DG - Design-Goals, F – Functions, P – processes, S - systems

21 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 K P Mind Cell Elementary IPK Computational Model (Information, Preferences, Knowledge) Copyright High-Intelligence & Decision Research Group, CAMO, ENEA, Adam M. Gadomski, 28/09/2003http://erg4146.casaccia.enea.it

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

23 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 TasksActions IA En carrier relation Intelligent Agent World Copyright High-Intelligence & Decision Research Group, CAMO, ENEA, Adam M. Gadomski, 28/09/2003http://erg4146.casaccia.enea.it 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.

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

25 SCE Ontological Tools -TOGA Adam Maria Gadomski, erg4146.casaccia.enea.it/ High-Intelligence & Decision Research Group 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

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

27 INTELLIGENT DECISION SUPPORT FOR RESEARCH MANAGEMENT Copyright High-Intelligence & Decision Research Group, CAMO, ENEA, Adam M. Gadomski, 28/09/2003http://erg4146.casaccia.enea.it Situation Assessment & Decision Making is based on: Information: DOMAIN status, Knowledge: rules, procedures, instructions, Preferences: role criteria, risk criteria, resources criteria,... INTELLIGENT DECISION SUPPORT SYSTEM SIGRE link to computer networks Periodical monitoring MIND Sc. Tasks Continuous monitoring Financial & Decisional Requests/constrains Research Activities Actions Strategic Activities Administrative Activities Information EXAMPLE

28 Conclusions Adam Maria Gadomski, erg4146.casaccia.enea.it/ High-Intelligence & Decision Research Group 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 3 rd 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.

29 Conclusions Adam Maria Gadomski, erg4146.casaccia.enea.it/ High-Intelligence & Decision Research Group HID Anticipatory extrapolations Extrapolation of the current trends in three basic macro-engineering domains. [US Sources, DARPA, Web, 2000] Future Grow in Arbitrary Units Current name is Socio- Cognitive Engineering

30 References Adam Maria Gadomski, erg4146.casaccia.enea.it/ High-Intelligence & Decision Research Group HID 1A.M. Gadomski, Lectures on Safety and Reliability of Human-Machine Systems. Materials of SA-EUNET EU Project, 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. 3A.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), Gen., Rome, 1993, Publisher ENEA, Feb 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, 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, 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, A.M.Gadomski, Socio-Cognitive Scenarios for Business Intelligence Reinforcement: TOGA Approach, The paper preliminary accepted for publication in "Cognitive Science,Springer V For more information see :


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