5 July 2006
ENEA Sede
Roma
CRESCO Subproject III 4:
CRESCO-SOC-COG
Socio-Cognitive Modelling for Complex
Socio-Technological Networks
(Modellistica delle Reti Complesse viste come Aggregati Socio-Tecnologici e Cognitivi)
Strategies, Competences and Objectives
Alessandro D'Ausilio (ECONA), Massimiliano Caramia (Tor Vergata)
Adam Maria Gadomski (ENEA), Alessandro Londei (ECONA), Marta
Olivetti-Belardinelli (ECONA)
English Extended
Version
(Ed. A.M.Gadomski)
20 November 2006
CRESCO, Sottoprogetto III 4:
CRESCO-SOC-COG
1. Objectives and General Strategy (A.M.Gadomski)
2. ECONA (A. Londei, M. Olivetti-Belardinelli, D'Ausilio )
- general information
- competences
- specific research interests
- state of the art and the contribution
3. TOR VERGATA ( M. Caramia)
- general information
- competences
- specific research interests
- state of the art and the contribution
4. ENEA (A.M.Gadomski)
- competences
- project planning
- examples
CRESCO, Sottoprogetto III 4:
CRESCO-SOC-COG
CRESCO is a large ENEA's and Italian Project focused on the research on
complex systems in the different areas of science and technologies. It is based
on the development of the advanced High Performance Computing
infrastructure ENEA grid.
CRESCO (Centro Computazionale di RicErca sui Sistemi Complessi,
Computational Research Center for Complex Systems) is co-funded by the
Italian Ministry of Education, University and Research (MIUR).
The CRESCO project is functionally built around the HPC platform, through
the creation of a number of scientific thematic laboratories, such as:
Computing Science Laboratory, Computational Systems Biology Laboratory,
and Complex Networks Systems Laboratory - dealing with the complexity of
information technology networks and human organizations decisional
dependences in large national critical services infrastructures.
A major ambition of this multi-discipline project is to allow an inter-disciplinary
flow of methods and ideas related to the network-based modeling and
simulation of complex systems and their aggregates.
Sottoprogetto III 4:
CRESCO-SOC-COG
Objectives and General Strategy
CRESCO-SOC-COG is the activity focused on the research on the
vulnerabilities of human factors in frame of networked structures of high-risk
large human organizations.
This new challenging cross-disciplinary objective requires a qualitatively new
systemic conceptualization tool for human-technology systems, therefore, the
socio-cognitive methodology involved is based on the main frameworks of the
holistic TOGA meta-theory.
Goal
Research and development of the ontology and socio-cognitive and
socio-technological models which should enable:
 Domain-independent computational modelling and demonstrative simulation
of socio-cognitive managerial high-risk decisional processes and their
interdependences. Especially in the case of the collaborative emergency
management for the protection of Large Complex Critical Infrastructures
(LCCI).
 ModelIing and analysis of the socio-cognitive vulnerabilities of these
organizations.
Sottoprogetto III 4:
CRESCO-SOC-COG
Objectives and General Strategy
Identification of the Domain
Decisional Politic
Organs
Top-Down Vision :
Local
administrative,
govern and
voluntary
organizations
LCCI Owners
Large Technological Networks- LCCIs
Utenti di GRT
Socio-Technological
network for the
management of Large
Critical Technological
Infrastructures
Sub-project III 4:
CRESCO-SOC-COG
Objectives and General Strategy
“Spetroscopy” of the conceptualization layers
Identification
Layers:
 Physical Layer
 Cyber/information Layer
 Organization /
Management Layer
Sub-layers:
Cognitive –Sub-simbolic Layer
Socio-cognitive Simbolic Layer
Inter-organization Layer
Intra-organizational Layer
Their interfaces
Sottoprogetto III 4:
Multimedial Interfaces
between Cyber and
Organization Layer
CRESCO-SOC-COG
(Ferov di Stato, L’espresso, 2006)
Tasks Separation
Topological & process data
Tasks & Actions data
Vocal Communication
Written Tasks & Inform.
Cyber
Layer
Organization
Layer
Sottoprogetto III 4:
CRESCO-SOC-COG
Conceptual Scenario-based Interface: An introduction to the
CIP (Critical Infrastructure Protection) ontology
Operator is an autonomous informer
and executor, see UMP.
Operators are human interfaces
between Cyber and Organization
Layers.
Organization Layer is activated
when the situation is over the
(routine & emergency)
competences of the operators
Organization decisions provide
context and constrains for next
organizational decisions.
Adam M. Gadomski, CAMO – ENEA – RC Casaccia
CRESCO-SOC-COG
Sottoprogetto III 4:
Socio-Cognitive Domain
Socio-Cognitive
and
Socio-technological layers
Socio-Technological Domain
Organiz. A
Organiz. B
D-M autonomo
…
R
5
Subsymbolic D-M
zoom
R
1
Symbolic D-M
Separation of
two conceptual
domains of
research.
R
3
D-M collaborativo
R
6
R
2
R
4
R
7
Simulation: Piattaforme parallele
software di supporto D-M : tecn.
“multiagent” (MAS)
Nodi esecutivi
Legenda:
Ri
Nodi decisionali
manageriali
Ri – ruolo i
Reti di Grande Infrastrutture
Tecnologiche dei Servizi
Unita umane supportate dal IT
Sottoprogetto III 4:
CRESCO-SOC-COG
Strategia Generale : ORGANIZATION COMPLEXITY
Multi-dimensional attributes space
Complex network of interactions
Continuous & Discrete Dynamics
Physics based
statist. models
(primitive
intelligence)
Interactions with dynamic physical & social environment
Intelligent knowledge-based and interest-based human nodes
Autonomy of nodes
Emotional and Body contribution components
Cognitive factors: ill measurable, observable and monitored
Project requires a new innovative computational
systemic methodology for the modeling.
Adam M. Gadomski, CAMO – ENEA – RC Casaccia
New
modeling
paradigms
(high
intelligence)
TOGA
meta-theory
Modelling Tool:
Top-down Object-based Goal-oriented Approach
TOGA is a formal goal-oriented knowledge ordering meta-theory, its objective is to enable
design of complex systems & their computer simulation. It has three basic components:
- Theory of Abstract Objects (TAO) is a first level and a basic domain independent
conceptualization system and a consensus building platform;
- Knowledge Conceptualization System (KNOCS), It includes TOGA’s ontology, i.e.
axiomatic assumptions and basic conceptualization frameworks for the definition and
decompositions of the real-world problem into an intelligent agent (IA) and domains of IA goaloriented activities, i.e. the triple: (Intelligent Entity, Environment, Interactions)
- Methodological Rules System (MRUS) for the specification (if not existing yet) or
identification (if existing) of complex systems and problems; it indicates how TAO and KNOCS
have to be used during the conceptual identification, specification and solution of real word
problems.
The KNOCS meta-frameworks includes four modeling paradigms:
1. Universal Reasoning Frame Paradigm (URP), it is based on the IPK (Information,
Preferences, Knowledge) architecture.
2. Universal Management Paradigm (UMP), it includes management functional
definition and a conceptualization of the context of the managerial role.
3. SPG Universal Domain Paradigm (UDP), it is a framework of the conceptualization
of the relation between an organization and its foundation-goal in terms of: systems, processes,
functions and design-goals.
4. WAG Universal Activity Paradigm (UAP) , conceptualization of the relation
between a problem world and a goal of intervention of intelligent agent .
[CNIP’06 Conf.]
Sottoprogetto III 4:
CRESCO-SOC-COG
Cognitive complex networks modeling
First project cog-engineering hypothesis:
Abstract Cognitive Architecture of DecisionMaker is based on 4 types of reasoning
processes reciprocally interacting and
developed on the recursive, incremental and
multi-layered IPK based network (with a
fractal property ).
TOGA
I
P
K
Domains of possible research
Subsymbolic
Not conscious reasoning
Conscious reasoning
 Neural Networks
 Images-Based Associations
 Genetic Algorithms
Symbolic
 Associative networks
 Procedural-relational networks
 Associative Networks
 Cause-consequence networks
 Model based network
Sottoprogetto III 4:
CRESCO-SOC-COG
Organizational complex networks modeling
Second project engineering hypothesis: Universal Management Paradigm
(UMP) defines the manager environment from the subjective perspective of a preselected decision-making manager [4] which can be projected on real role-networks
of human organizations.
SUPERVISOR/
COORDINATOR
tasks
information
cooperation
expertises
COOPERATING
MANAGER
MANAGER
ADVISOR
Knowledge &
Preferences
repository
information
INFORMER
tasks
with the same
relative internal
structure
EXECUTOR
DOMAIN OF ACTIVITY AND MANAGER’s GOAL-DOMAIN
Recursive
incremental
model
Sottoprogetto III 4:
CRESCO-SOC-COG
Identification of Vulnerability
The presented modeling frames enable identification of different types of organizational
vulnerability: on individual levels, for group d-m, and cooperative intra-organizational types.
Using IPK
Using UMP
SUPERVISOR
Domain of Activity
tasks
Vulnerabilities
information
n
cooperation
I
expertises
COOPERATING
MANAGER
MANAGER
ADVISOR
P
K
goal
Knowledge
Preferences
information
tasks
The
same
structure
We may distinguish:
INFORMER
- Not sufficient information
EXECUTOR
- Not proper preferences
-Not adequate competences (knowledge).
- Improper communication
Domain of management (Domain of activities)
Sottoprogetto III 4:
CRESCO-SOC-COG
Identification of Vulnerability
Human organization is a system/network with explicitly established reciprocal
dependencies between people, which, according to their competences, collaborate
for achieving common objectives or realize predefined missions.
The concepts: vulnerability, crisis and emergency are well visible in this generic h-orgnization
life-cycle picture where they can be, in different manner, allocated to the organization phases.
H-Organization Life-cycle
Foundation
Self-organization
Efficacy
Proper activity phase
Ef1
Re-organization
Vulnerability
Ef2
Proper Activity
Vulnerability
Re-organization
Crisis
Proper Activity
Ef0
Pathological organization
Healthy organization
Organization in recovery
Time
Self-org phase
Qualitative illustration Gadomski,2005,
We distinguish three necessary critical efficacy levels:
-Survive efficacy, Ef0. - Emergency critical efficacy, Ef1 - Routine critical efficacy, Ef2
(enables a bureaucratic functioning)
Sottoprogetto III 4:
CRESCO-SOC-COG
Partners
Top Tasks Allocation
Cognitive Layer
ECONA
Integration
Methodology
Socio-cognitive
Layer
ENEA
DII - TOR VERGATA
Socio-technological
Layer
Sottoprogetto III 4:
CRESCO-SOC-COG
ECONA (1) Interuniversity Center for Research on
Cognitive Processing in Natural and Artificial Systems
Informazione Generale
ECONA is an inter-university and
cross-disciplinary center providing
teaching staff and researchers in
which participate 12 Italian
universities.
ECONA collaborates with research projects (including
projects financed by MURST, CNR, the EEC and the
European Science Foundation) and covers the following
areas:
Psychology of cognitive processes
Mental process models
Neural networks and genetic programming
It is focused on the studies of cognitive
processes and collaborates on research
projects and their practical applications.
Non-linear dynamic behavior
Members of ECONA represent
inter-disciplinary competences:
psychology, philosophy, physics,
computer science, mathematics,
engineering, medicine and
organization sciences.
Psychophysiology and neuropsychology
Natural language processing
Logic, languages and methods in programming
Pedagogic communication
Education with intelligent processor support
Probabilistic approaches to situations of uncertainty
Learning processes
Sottoprogetto III 4:
CRESCO-SOC-COG
ECONA (2): Cognitive Perspective on Decision Making
Decision-Making
Tempo ridotto
Complessità della rappresentazione problemica
Stress e Responsabilità
ERRORE
Ma se non esiste una risposta sempre “Corretta”?
Sottoprogetto III 4:
CRESCO-SOC-COG
ECONA (3)
IMPLEMENTATION
•
Situazioni artificiali e semplificate
> controllo
< aderenza realtà
•
Situazioni reali
< controllo
> aderenza realtà
Sottoprogetto III 4:
CRESCO-SOC-COG
ECONA (4)
SCOPI
Individuare classi di risposte divise per tipologie di
personalità DECISONALI
• Strategie Analitiche VS. Globali (Complexity)
• Fast VS Slow responder (Time)
• Strategie di Coping (Stress, responsibility)
Sottoprogetto III 4:
CRESCO-SOC-COG
ECONA (5)
QUANDO - COME - PERCHE’
si commettono errori
• Previsione errori “macchina” uomo
• Supporto decisionale situazioni critiche
• Controllo in real-time
• Simulazione effetti della decisione
Sottoprogetto III 4:
CRESCO-SOC-COG
ECONA (6)
from 
SOM
Cluster
Analysis
Behavioral prototypes
from TOGA
Sottoprogetto III 4:
ECONA (7)
CRESCO-SOC-COG
Automatic Model Generation Possibility
Genetic algorithms
genetic
population
Plasticity
selection
fitness
crossing-over
mutations
next
population
Architecture
selection
Sottoprogetto III 4:
ECONA (8)
CRESCO-SOC-COG
Automatic Model Generation Possibility
• selection of the properties of artificial agents whose behavior
is compatible with natural observation
• decisional-making is under/(driven-by) environmental pressure
• determination of suitable recurrent neural architectures for
best results by means of genetic algorithms
• analysis of neural spatial and functional distribution for
detecting functional areas involved in decisional task
• extension to socio-cognitive networks of evolved agents
Sottoprogetto III 4:
ECONA (9)
CRESCO-SOC-COG
From Cognitive Models to Socio-Cognitive Networks
Decisional agents
genetic modelization
Fastness
Efficency
Behavioral support to
psychological and artificial
observations
Sottoprogetto III 4:
CRESCO-SOC-COG
Dipartimento di Ingegneria dell’Impresa
Università di Roma “Tor Vergata”
Competenze e Aree principali di ricerca
• Modellazione dei processi gestionali
• Ottimizzazione e simulazione di sistemi complessi
• Ottimizzazione su reti
• Metodi e modelli per il supporto alle decisioni
• Logistica e Produzione
Sottoprogetto III 4:
CRESCO-SOC-COG
DII - TOR VERGATA
• Interesi particolari riferiti ai goal del progetto
– Ottimizzazione in ambiente on-line
– Modellazione di sistemi di produzione-servizio tramite agenti autonomi
– Modellazione di problemi decisionali in presenza di più decisori con
presenza o assenza di cooperazione e/o negoziazione
– Simulazione di sistemi organizzati in scenari tattici e/o operativi
• Risorse: professori, post-doc, laureandi
Sottoprogetto III 4:
CRESCO-SOC-COG
DII - TOR VERGATA
ESPERIENZA PREGRESSA
• Esperienza in progetti su argomenti correlati: Progetto Strategico
CNR su “La gestione delle emergenze nelle organizzazioni
complesse”; 9 unità perative coordinate da Tor Vergata; anni
2000-2002.
• Conoscenza e uso dei diversi Strumenti di Progettazione
Concettuale.
Sottoprogetto III 4:
CRESCO-SOC-COG
DII - TOR VERGATA:
Possible Contributions
Case Based Analysis e Modellazione
• Analisi di casi reali scelti e la modellazione sintetica
(organizational networks)
• Simulazione (tipo demo) di casi di studio relativi a situazioni di crisi
rilevanti in cooperazione tra organizzazioni complesse, al fine di
individuare le cause di vulnerabilità e definire le azioni correttive al
loro interno.
• Attività successive proposte: prototipizzazione del tool di
simulazione con possibilità da parte dell’utente di effettuare
opportuni tuning del sistema per il suo controllo.
Sottoprogetto III 4:
CRESCO-SOC-COG
ENEA
Keywords:
•
competences
•
•
planning
esamples
Systemistic Modelling and Top-down approach
Socio-Cognitive Engineering
Meta-Knowledge Engineering & Management
Decision-Making
Intelligence
Ontology Building Methodology
Abstract Intelligent Agents
Organizational Intelligence
Organizational Vulnerability
Simulation Modelling
Sottoprogetto III 4:
CRESCO-SOC-COG
ENEA
PLANNING
1. Data & Modeling phase
2. Designing & Implementing phase
3. Improvement & Validation phase
1. Data & Modeling
phase
- Data acquisition
- Proper modeling
- Model validation
2. Designing &
Implementing
phase
- Parallelization
- Implementation
- Validation
3. Improvement &
Validation phase
- Improvements
- Test cases
- Validation
Sub-project III 4:
CRESCO-SOC-COG
ENEA
Data Acquisition: EXPERIMENTS
For Cognive DecisionMaking
For Organizational DecisionMaking
Identification of Socio-Cognitive
Vulnerabilities
Sottoprogetto III 4:
CRESCO-SOC-COG
EXAMPLE: an identification of the Incidents and their main observables
(Key factors)
Source: L’espresso, 6 Luglio 2006
Sottoprogetto III 4:
•
CRESCO-SOC-COG
EXAMPLE: an identification of the key factors of human errors:
…IPK  65%
METHODOLOGICAL Framework
We have:
Experimental observables and
Theory observables.
Experimental observables
Experimental factors (key factors)
Preference
Informazioni
Domain Model
Theory Ontology
Conoscenza
Theory observables
MODEL SPECIALIZATION
Source: L’espresso, 6 Luglio 2006
SIMULATIOR DESIGN
Sub-project III 4:
CRESCO-SOC-COG
ENEA
Analyzed Test Cases
1. Blackout Italy/Suisse , 28 september 2003
2. Chernobyl disaster
3. Katrina hurricane
4. Airport Linate accident
5. Tsunami: international scale catastrophe –Indian
Ocean
P,Sargeni, L’ergonomia cognitiva nella vulnerabilità delle organizzazioni: la
prospettiva socio-cognitiva di TOGA. Facolta Science di Comunicazione, Univ.
La Sapienza.,ENEA, 2006.
Sub-project III 4:
CRESCO-SOC-COG
Preliminary Test Cases Results
Identification of vulnerability on the IPK level and according to the UMP roles.
Ruoli
Casi
Supervisor
Manager
Cooperating
Manager
Advisor
Informer
Italian
Blackout
Chernobyl
Linate
Katrina
Tsunami
Legenda:
Il problema si è verificato sul livello delle Informazioni
Nessun valore dominante
Il problema si è verificato sul livello delle Preferenze
Il problema si è verificato sul livello delle Conoscenze
[P,Sargeni ]
Executor
Sub-project III 4:
CRESCO-SOC-COG
Possible results hypotheses
How, is possible to improve organiz,
robustness/(decrease vulnerability)?
Hypotheses:
- by modifications of organization architecture
- by modifications of roles (competences, responsibility, power)
- by increasing of the consciousness on the emotional components of DM
-- computer support, automatic distribution IPK in organization according
to the organizational roles of nodes.
-- Providing these structures more transparent
-- Modification and adaptation of distributed DM procedures
Sub-project III 4:
CRESCO-SOC-COG
References
•
Jens Rassmussen, 1988. A cognitive engineering approach to the modeling of decision making and its
•
A.M. Gadomski (2004). Humam Organization Crisis: Identification, Response & Recovery,
http://192.107.74.146/gad-crisis.htm
A.M. Gadomski, 2002, Systemic Approach for the Sophocles Global Specification,.
http://hid.casaccia.enea.it/RepSoph-v10.pdf
http://erg4146.casaccia.enea.it/wwwerg26701/Gad-toga.htm
R.J. Sternberg, Triarchic Theory of Intelligence,.
Student theses:
D. Ricciardi, Analisi della vulnerabilità del business aziendale e del Knowledge Management
secondo la prospettiva della teoria TOGA, 2005,, Univ. Tor Vergata.
P,Sargeni, L’ergonomia cognitiva nella vulnerabilità delle organizzazioni: la prospettiva sociocognitiva di TOGA. Facolta Science di Comunicazione, Univ. La Sapienza, 2006.
Selected ENEA’s materials of the IRRIIS Project, 2006
L’ESPRESSO., N.26, 6 Lug. 2006
Web:
- Google search: CIIP, CIP, cognitive:
http://www.google.it/search?hl=it&q=CIIP%2C+CIP%2C+cognitive&btnG=Cerca&meta=
– the European co-ordination project on Critical Information Infrastructure Research Coordination. http://www.ci2rco.org/index.asp
– http://w3.uniroma1.it/security/Eventi/Sciascia.pdf
– www.cnipa.gov.it/site/_files/pres-MEROLAroma.PPT
– Activity progress report: Relazione sulle attività svolte dall'ENEA -CAMO, 2005 :
http://hid.casaccia.enea.it/activity2005.htm
•
•
•
•
•
•
…
organization in process control, emergency management, CAD/CAM, office systems, and library systems.
Advances in Man-machine Systems Research 4: 165--243
Sub-project III 4:
CRESCO-SOC-COG
References
ECONA
DII-U.Tor
Vergata
Sub-project III 4:
CRESCO-SOC-COG
Grazie