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Operational process models for crisis management

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Title: Operational process models for crisis management


1
Operational process models for crisis management
  • Prof. dr. T.J. Grant
  • T 31 (0)76 52 73261 (Mon-Wed)
  • M 31 (0)638 193 749
  • TJ.Grant_at_nlda.nl

2
Outline
  • Goal
  • To survey operational process models, showing
    use as basis of IS architecture team
    organisation
  • Structure
  • Introduction
  • Process models
  • OODA, SHOR, Rasmussen, PDCA
  • Team models
  • (Tea break)
  • Rational reconstruction of OODA (OODA-RR)
  • OODA-RR team organisation
  • OODA-RR IS architecture
  • OPERATION BEACH TOWEL (if time permits)
  • Current future research

3
Introduction myself
  • Qualifications
  • BSc Aeronautical Engineering, Bristol, UK
  • Defence Fellowship (Masters), Brunel, UK
  • PhD Artificial Intelligence, Maastricht, NL
  • Experience
  • 1966-87 Royal Air Force officer, UK SG
  • 1987-2004 ICT consultant, Atos Origin, NL
  • Dutch-French ICT company aerospace, defence,
    road traffic
  • 2001-date Professor, U. Pretoria, ZA (20)
  • Computer Science Department ICT for Planning
    Control
  • 2004-date Professor, NLDA, Breda, NL (50)
  • Operational ICT Communications

4
Introduction NLDA (1)
  • NLDA Netherlands Defence Academy
  • Mission
  • Educate men women to become professional
    motivated officers in a dynamic military
    organization
  • Scientific research in military focus areas for
    knowledge development, education, policy advice
  • Ambition
  • To become accredited as a university under
    European regulations in 2008-9

5
Introduction NLDA (2)
Faculty Board Dean
Research office
Faculty office
International Security
SEWACO systems
Military Behavioural Sciences Philosophy
Military History General Strategy
Platform systems
Management, Organisation Defence Economics
Navigation
Military Operations
Logistics Information
Military Sciences
Management Control Sciences
Technical Sciences
6
Introduction architectural context
Operational needs impose requirements on
technical implementation
New ICTs make new types of operation possible
ICT Information Communications
Technology (i.e. IT communications)
7
Process models (1) motivation
  • Motivation for tutorial
  • Seek commonalities across domains
  • Military Command Control (C2)
  • IS for crisis response management
  • Process control
  • (more)
  • Construct scientific model for commonalities
  • Operational process model is one of these
  • Opens up possibilities
  • Scientific exchange ideas across domains
  • Operational enables across-domain
    interoperability
  • Commercial enlarges market for COTS products

8
Process models (2) examples
9
Process models (3) examples
Combined Air Operations Center
Command Centre onboard frigate
Collaborative process
Army Command Post
10
Process models (4) characteristics
  • Complex real world in which
  • Goals tasks ill-defined may conflict
  • Situation changes over time
  • Multiple players nobody in overall control
  • Real-time loop between actions feedback
  • High stakes
  • Information uncertain, ambiguous, incomplete
  • Decision makers have knowledge expertise
  • Decision makers under time stress

Klein Klinger, 1991
11
Process models (5) definitions
  • Command Control (C2)
  • Command and control can be viewed as directing
    the process of operations by means of efficient
    and effective application of resources at hand in
    order to achieve a given mission
  • C2 system
  • An assembly of equipment, methods and procedures
    and, if necessary, personnel, that enables
    commanders and their staffs to exercise command
    and control
  • N.B. Not just ICT, but also people procedures
  • C.f. DCMOTP factors
  • Doctrine, C2, Materiel, Organization, Training,
    Personnel

12
Process models (6) Controllers task
13
Process models (7)
  • What is a process model?
  • A model of thinking processes of decision-making
    team in crisis management operations
  • Compare business process model
  • Where do you find them?
  • Cybernetics literature
  • Psychological literature
  • Human supervisory control literature
  • Organisation management theory
  • Military C2 literature
  • ISCRAM literature?? TIEMS??

14
Process models (8)
  • What are process models useful for?
  • IS architecture (operational view)
  • Organising decision-making team
  • Selecting training team members
  • (Self-) evaluation of team effectiveness
  • Layout of control centre
  • Data exchange standards protocols
  • Providing infostructure

15
Process models (9)
  • History of process models
  • Late 1970s / early 1980s
  • Task-oriented process models
  • At least 16
  • All descriptive variants on the control loop
  • From environment thru sensors, control, to
    actuators
  • Each process model can be mapped to others
  • Since 2000
  • Flurry of interest in
  • Applying task model to IS
  • At least 6 all OODA-based
  • Adding team / collaboration model
  • At least 9

Mayk Rubin, 1988
16
Process models (10) theory
(Adapted from) Ashby, 1963
17
Process models (11) theory
  • Control (informal definition)
  • Monitoring influencing actions / events
  • Process Under Control (PUC)
  • Hardware, software and/or humans
  • Usually regarded as (finite?) state machine
  • Inputs from environment (via sensors)
  • Outputs to environment (via actuators)
  • Internal states
  • Controlling Process (CP)
  • Goal-directed (objectives)
  • HW SW maybe also humans (controllers)
  • Human supervisory control
  • Not in contact with environment only via PUC

18
Process models (12) theory
Objectives
instructions
observations
Controlling process
Process Under Control
inputs
outputs
19
Process models (13) theory
20
Process models (14)
  • Process models surveyed
  • OODA (Boyd)
  • SHOR (Wohl)
  • Rasmussen
  • RPDM (Klein)
  • SA (Endsley)
  • PDCA (Shewhart / Demming)
  • HEAT (Lawson)
  • Other surveys
  • Mayk Rubin, 1988 15 models (incl. SHOR)
  • Brehmer, 2005 4 models (incl. SHOR HEAT)
  • Essens et al, 2005 8 models

21
Process models (15) Boyds OODA
  • History
  • Source
  • Boyd, J.R. 1987. An Organic Design for Command
    and Control. In A Discourse on Winning and
    Losing. Unpublished lecture notes
  • USAF Col. John Boyd
  • 1927-1997
  • 1945-47 Enlisted in US Army Air Corps
  • 1951-75 USAF officer
  • Fighter pilot
  • Served in Korean Vietnam wars
  • 1954-60 Fighter Weapons School
  • Forty-Second Boyd
  • Proud of description as maverick thinker

22
Process models (16) Boyds OODA
  • History (continued)
  • Birth of OODA loop
  • Small part of Boyds overall thesis
  • Energy manoeuvrability
  • Fighter design (F.15 F.16)
  • Air-to-air tactics
  • OODA based on his observation of dog-fights
  • Idea advocated by 15-hour/2-day briefings
  • Patterns of Conflict
  • A Discourse on Winning and Losing (327 slides)
  • Idea rejected by USAF till 1991 Gulf War
  • Adopted enthusiastically by US Marines

23
Process models (17) Boyds OODA
Observe
Orient
Decide
Act
Observations
Note how orientation shapes observation, shapes
decision, shapes action, and in turn is shaped by
the feedback and other phenomena coming into our
sensing or observing window. From The Essence of
Winning and Losing, John R. Boyd, January 1996.
24
Process models (18) Boyds OODA
Observe
Orient
Decide
Act
Plan
Plan
ImplicitGuidance Control
ImplicitGuidance Control
UnfoldingCircumstances
CulturalTraditions
Observations
Decision(Hypothesis)
GeneticHeritage
Analyses Synthesis
Action(Test)
FeedForward
FeedForward
FeedForward
NewInformation
PreviousExperience
OutsideInformation
UnfoldingInteractionWithEnvironment
UnfoldingInteractionWithEnvironment
Feedback
Feedback
25
Process models (19) Boyds OODA
  • Observe
  • Collect sensor observations of PUC environment
    ( CP)
  • Orient/Assess
  • Filter observations according to expectations
  • Identify situation(s) matching filtered
    observations
  • Decide
  • Select suitable response to identified situation
  • Act
  • Implement selected response generate
    expectations
  • Often means issuing instructions to sensors
    effectors
  • Plan
  • Develop options for multiple situations
    predict future states

26
Process models (20) Boyds OODA
  • Key features of Boyds OODA model
  • Centrality of Orient (Situation Awareness)
  • Only process shown in detail in Boyds (1996)
    figure
  • In Boyds words
  • Note how orientation shapes observation, shapes
    decision, shapes action, and in turn is shaped by
    the feedback and other phenomena coming into our
    sensing or observing window.
  • Tempo In Boyds words
  • In order to win, we should operate at a faster
    tempo or rhythm than our adversaries or, better
    yet, get inside the adversary's
    Observation-Orientation-Decision-Action (OODA)
    loop.

27
Process models (21) Boyds OODA
  • Situation Awareness (SA)
  • Perception of elements in environment within a
    volume of time and space, comprehension of their
    meaning, and projection of their status in near
    future
  • A.k.a. having big picture or helicopter view
  • Knowing what is going on around me NOW
  • Levels
  • Perception of elements in environment PUC
  • Comprehension combine, interpret, store
    information
  • Prediction forecast future events what-if
    simulation
  • SA determines capacity to decide act
  • Good SA depends on
  • Receiving information from diverse sources
  • Evaluating it quickly
  • Distributing it to dispersed units

Endsley, 2000
28
Process models (22) Boyds OODA
  • C2 decision making
  • Rational decision-making (1940s-1985)
  • Enumeration ranking of options (decision
    theory)
  • Rational (optimising) decision makers
  • Option selection process central
  • Pro proven optimal
  • Con needs perfect information unlimited time
  • Naturalistic decision-making (1985 on)
  • Single-option, pattern matching simulation
  • Experienced decision makers in natural
    environment
  • Situation assessment (Orient) central
  • Pro fast / time limited robust under
    uncertainty
  • Con satisficing / not optimal human errors /
    biases

Raiffa, 1968
Klein, 1998
29
Process models (23) Boyds OODA
  • Influence of OODA
  • Military
  • OODA underlies
  • Manoeuvre warfare
  • AirLand battle
  • Shock and awe
  • Network-centric warfare
  • Civil
  • Harvard Business Review article, 1988
  • Adopted by
  • Toyota, Nokia, GE, Intel
  • Multiple variants in C2 literature

30
Process models (24) Wohls SHOR
  • History
  • Source
  • Wohl, F.G. 1981. Force Management Decision
    Requirements for Air Force Tactical Command
    Control, IEEE Transactions on Systems, Man and
    Cybernetics, SMC-11, 9, 618-639 (September 1981)
  • Wohl
  • Psychologist
  • MITRE Corp.
  • SHOR model
  • Many influences (see p.625)
  • Decomposed into sub-processes (see Fig. 7)
  • Maps closely to OODA
  • See Grant Kooter (2005)
  • However, Wohl Boyd do not seem to have been
    aware of each others work

31
Process models (25) Wohls SHOR
Triggering event (deadline, enemy action, new
data, etc)
Stimulus
Response
Hypothesis
Option
Environment
Raw or pre-processed data
Action or communication
Antagonists
Protagonists
32
Process models (26) Wohls SHOR
  • Influence of Wohls paper
  • Much cited
  • Largely for Tactical Decision Process (not SHOR)
  • Easily accessible in open literature
  • Not spawned other areas of research
  • (unlike Rasmussen)

33
Process models (27) Rasmussen
  • History
  • Source
  • Rasmussen, J. 1983. Skills, rules and knowledge
    signals, signs and symbols, and other
    distinctions in human performance models, IEEE
    Transactions in Systems, Man and Cybernetics,
    SMC-13, 3, 257-267 (May/June 1983)
  • Rasmussen
  • Psychologist
  • Worked with W.B. Rouse human diagnosis
  • Riso National Laboratory
  • Three-level model
  • Stimulus-Response theory (Skinner)
  • Roots in diagnosis
  • If experience doesnt work, use 1st principles
  • Influenced by Artificial Intelligence
  • IF-THEN rules (expert systems)

34
Process models (28) Rasmussen
skill based (signals)
Rasmussen, 1983
35
Process models (29) Rasmussen
  • Influence of 3-level model
  • Analysis of control task
  • Task analysis
  • Matching levels of decision support
  • User interfaces
  • Sources of human error
  • Reasons GEMS model
  • Training
  • Multi-agent systems
  • 3-tier (3T) architecture
  • Used 2 levels (rule knowledge) in my PhD

36
Process models (30) Rasmussen
knowledge based (symbols)
37
Process models (31) PDCA
  • History
  • Sources
  • Shewhart. 1939. Statistical Method from the
    Viewpoint of Quality Control
  • Demming. 1951. The New Way. In Elementary
    Principles of the Statistical Control of Quality,
    Nippon Kaagaju Gijutsu Remmei, Tokyo, Japan
  • Shewhart
  • 1891-1967
  • Statistical control (in manufacturing)
  • Origin of PDCA
  • Shewharts 1939 book
  • Demmings role
  • Management by position cooperation 14 points
  • Champion of Shewharts ideas Shewhart Cycle
  • Introduced 4th step, 1951

38
Process models (32) PDCA
Plan
Do
Act
Check
39
Process models (33) PDCA
  • Plan
  • Determine goals targets
  • Determine method of reaching goals
  • N.B. Combines OODAs Plan Decide
  • Do
  • Engage in education training
  • Implement plan (c.f. Act in OODA)
  • Check
  • Check effects of implementation
  • N.B. Sometimes called Study (PDSA)
  • Act
  • Take appropriate action
  • N.B. Not same as Act in OODA learning process

40
Process models (34) PDCA
  • Influence of PDCA
  • Quality control
  • Management theory
  • Widely used by management consultants
  • Information computer security
  • BSI 17799

41
Process models (35) comparison
42
Team model communication
Received Signal
Signal
Message
Message
Information source
Transmitter
Receiver
Destination
Noise source
Adapted from Shannon, 1948
43
Team model OODA-based
Information distribution
Shared awareness
Team maintenance task (re-)allocation
Confirmation authorisation
Adapted from Keus, 2002
44
Team model CTEF (1)
Essens et al, 2005
45
Team model CTEF (2)
  • Task-focused behaviours
  • Managing information
  • Obtaining information
  • Processing information
  • Exchanging information
  • Assessing situation
  • Making decisions
  • Planning
  • Directing controlling
  • Liaising with other command teams
  • Maintaining common knowledge

Essens et al, 2005
46
Team model CTEF (3)
  • Team-focused behaviours
  • Providing maintaining vision
  • Maintaining common intent
  • Interacting within team
  • Communicating
  • Coordinating
  • Providing feedback
  • Motivating
  • Adapting
  • Monitoring
  • Correcting (offering feedback / guidance)
  • Backing-up (supporting with compensatory
    behaviours)
  • Providing team maintenance

Essens et al, 2005
47
OODA-RR (1) OODAs shortcomings
  • Neither detailed nor formalised
  • No guarantee of scalability
  • Other agents not modelled explicitly
  • Competitive interactions only
  • Lacks psychological validity
  • No domain state or world model
  • No concept of attention or memory
  • Lacks deliberative planning process
  • Lacks learning process
  • Not published in accepted scientific way
  • Has been subjected to peer review

Grant Kooter, 2005
48
OODA-RR (2) need for RR
  • OODA influential as mental model
  • Describes decision-makers thinking process
  • But is it suitable as IS architecture?
  • Indication is positive (N.B. as operational view)
  • User-centred design
  • Suitability needs testing (research)
  • Rational reconstruction essential
  • Using SADT/IDEF0 UML notation
  • Using systematic set of use-cases
  • In context of C2 architecture standards
  • E.g. DoD Architecture Framework ATCCIS

49
OODA-RR (3) RR approach
  • Rational reconstruction
  • Systematic translation of intuitive knowledge
    into logical form
  • Reconstructing OODA
  • Identify shortcomings
  • Define requirements
  • Define top-level use-cases
  • Select notation
  • Formalise process model, walking through
    use-cases
  • Implement
  • Evaluate

Habermas, 1979
50
OODA-RR (4) requirements
  • Requirements
  • Retain 4 processes as core functionality
  • Add planning learning processes
  • Emphasise concurrent processing
  • Provide rule- knowledge-based levels of
    reasoning
  • Base decomposition on RPDM for validity
  • Represent real-time aspects (tempo)
  • Explicitly show agent boundary
  • Allow multiple, human and/or machine agents
  • Permit competitive and/or collaborative
    relationships

51
OODA-RR (5) use-cases
  • Use-cases

52
OODA-RR (6) the model
Set Filter
Observation
Observing
Retrieve alternative COA
Signal
Goals
Goals
Orienting
Unexpected situation
Sensors
Expected Situation
Control of planning
Accepted goal
Prototypes
Planning
Plans
Assessors
Observed prototypes
Construct COA
Effects achieved
Prototypes
New/modified Prototype
Environment
Planners
Deciding
Situation not recognised
Selected Plan
Decisionmakers
Control of Sensemaking
Existing prototypes
Sensemaking
Acting
Sensemakers
Actuators
COAs
Expectations
Actions
53
OODA-RR (7)
  • Processes
  • Observing
  • Collecting observations
  • Orienting
  • Assessing situation using Prototypes creating SA
  • Planning
  • Developing courses of action (COA) based on SA
  • Deciding
  • Selecting which COA to execute
  • Acting
  • Executing selected COA generating expectations
  • Sensemaking
  • Creating Prototypes from experience

54
OODA-RR (8)
  • Data structures
  • Observations
  • Raw observations / data (typically from sensors)
  • Situations
  • Assessed situations, matching Observations to
    Patterns
  • (selected) Plans
  • Courses of action ( action-sequences)
  • Goals
  • Desired future Situations / effects to be
    achieved
  • Prototypes
  • Templates describing Situation-patterns based on
    experience
  • Actions
  • Instructions / requests to PUC
  • Expectations
  • Expected Observations if PUC executes Actions
    correctly

55
OODA-RR for organising team (1)
  • Typically specialisation
  • By discipline
  • Logistics, transport, medical, etc
  • By organisation
  • Army, Navy, police, fire brigade, UN, Red Cross,
    etc
  • Leads to stove-pipes
  • Communications up/down hierarchies
  • Communication delays, noise distortion
  • Coordination only at top levels
  • Overloads top

56
OODA-RR for organising team (2)
  • Possibilities based on OODA(-RR)
  • One person does everything
  • Group sub-processes, one person per group
  • Combine Plan in Orient or in Decide
  • Group Observe Orient
  • Group Decide Act
  • One person per sub-process
  • Observe, Orient, Plan, Decide, Act, Sensemaking
  • Multiple people for important sub-processes
  • E.g. multiple people for Orient or for Plan
  • Deliberately omit sub-processes
  • Plan - purely reactive only 1 step look-ahead
  • Sensemaking - no learning or post-hoc

57
OPERATION BEACH TOWEL
58
OPERATION BEACH TOWEL (1)
  • We could run OPERATION BEACH TOWEL twice
  • Centralized operation
  • Control Post (CP) as master node
  • Nodes as (honest) slaves do (only) what CP tells
    them to do
  • Network-centric operation
  • No control cell / master node
  • Nodes as intelligent agents ( everyone is
    master)
  • Hand-simulation
  • You will simulate
  • OODA-RR processes in CP
  • PUC nodes (Barracks, Depot, APOE, SPOE, etc)
  • I will act as simulation controller
  • Start stop simulation
  • Simulation clock (in days)
  • Ensure nodes play according to their Rules of
    Engagement

59
OPERATION BEACH TOWEL (2)
  • Situation
  • Germlish tourists have overrun eastern Madeira
  • Madeirans have appealed for UN help
  • Dutch government has responded
  • 6000 policemen to round up Germlish tourists
  • Dutch Army logistics battalion
  • Three KC-10 aircraft for air transport Dutch AF
    personnel
  • Hired Queen Mary II for sea transport
  • Mission
  • To round up all Germlish tourists in eastern
    Madeira and to transport them back to Barracks in
    Netherlands in the shortest possible time

60
Strategic transportation concept
POE
POD
TOA
Operational Control
Transportation for strategic mobility
Air Sea
Road Rail Waterways
Road Bus Rail
61
OPERATIONAL COMMANDER
OPCO
TOA
CA
Strategic movement
Operational movement
Tactical movement
62
OPERATION BEACH TOWEL (3)
Madeira
Netherlands
CP
1d
1d
Barracks
APOE
APOD
AA1
KC-10s only
1d
2d
1d
TOA
2d
1d
1d
1d
7(2)d
Depot
SPOE
SPOD
AA2
QM II only
63
OPERATION BEACH TOWEL (4)
Madeira
Netherlands
  • Network-centric communications
  • Anyone can query or make request of anyone else
  • Can broadcast queries / requests (e.g. Who has
    X?)

1d
1d
Barracks
APOE
APOD
AA1
KC-10s only
1d
2d
1d
TOA
2d
1d
1d
1d
7(2)d
Depot
SPOE
SPOD
AA2
QM II only
64
OPERATION BEACH TOWEL (5)
  • Compare the two runs
  • Differences in communication patterns?
  • Topology / connectivity
  • Communications workload
  • Differences in cognitive patterns?
  • Planning effort?
  • Decision-making effort?
  • Workload?
  • Differences in effectiveness?
  • Completeness of awareness of the situation?
  • Quality of decision-making?
  • Differences in efficiency?
  • How quickly were first Germlish tourists
    evacuated?
  • How long before all Germlish tourists were
    evacuated?

65
OPERATION BEACH TOWEL (6)
  • Allocating roles
  • PUC nodes
  • The leader (Decide)
  • I wanna be the leader
  • I wanna be the leader
  • Can I be the leader?
  • Can I? Can I?
  • Promise? Promise?
  • Yippee, Im the leader
  • Im the leader
  • OK what shall we do?
  • Roger McGough (b. 1937)
  • Rest of CP nodes

66
OPERATION BEACH TOWEL (7)
Madeira
Netherlands
1d
1d
Barracks
APOE
APOD
AA1
KC-10s only
1d
2d
1d
TOA
2d
1d
1d
1d
7(2)d
Depot
SPOE
SPOD
AA2
QM II only
67
End ofOPERATION BEACH TOWEL
68
OODA-RR for IS architecture (1)
  • Two choices
  • Implement OODA-RR (at operational level)
  • Decompose OODA-RR implement
  • E.g. Crew/Operator Support POLicy (COSPOL)
  • Based on analysing 12 implemented C2 systems
  • Implemented for ESA in Advanced Crew Terminal

Grant, 2002
69
OODA-RR for IS architecture (2)
  • On-going research
  • Key question
  • Is OODA a good basis for C2 system architecture?
  • Intuition
  • Systems based on users mental model have higher
    useability acceptance
  • Users mental model (in military C2) OODA
  • Running projects
  • HackSim 2 Masters students at Univ. Liverpool
  • Future projects
  • Hierarchical vs. network-centric connectivity
  • Speed-up planning by 1 OOM
  • Implement Sensemaking (from my PhD)

70
References (1)
  • Ashby, W.R. 1963. An Introduction to
    Cybernetics. John Wiley Sons, New York
  • Boyd, J.R. 1987. An Organic Design for Command
    and Control. In A Discourse on Winning and
    Losing. Unpublished lecture notes
  • Brehmer, B. 2005. The Dynamic OODA Loop
    Amalgamating Boyds OODA Loop and the Cybernetic
    Approach to Command and Control. In Proceedings,
    10th International Command and Control Research
    Technology Symposium, McLean, VA, USA
  • Brehmer, B. 2006. One Loop to Rule Them All. In
    Proceedings, 11th International Command and
    Control Research Technology Symposium, Cambridge,
    UK
  • Demming. 1951. The New Way. In Elementary
    Principles of the Statistical Control of Quality,
    Nippon Kaagaju Gijutsu Remmei, Tokyo, Japan

71
References (2)
  • Endsley, M.R. 2000. Theoretical Underpinnings of
    Situation Awareness. In Endsley, M.R., Garland,
    D.J. (eds). Situation Awareness Analysis and
    Measurement. LEA, Mahwah, NJ, USA
  • Essens, P., Vogelaar, A., Mylle, J., Blendell,
    C., Paris, C., Halpin, S., Baranski, J. 2005.
    Military Command Team Effectiveness Model and
    instrument for assessment and improvement. NATO
    RTO Technical Report AC/323(HFM-087)TP/59 (April
    2005)
  • Ferrell, W.R., Sheridan, T.B. 1967.
    Supervisory control of remote manipulation, IEEE
    Spectrum, 4, 81-88
  • Grant, T.J., Kooter, B.M. 2005. Comparing OODA
    and Other Models as Operational View C2
    Architecture. In Proceedings, 10th International
    Command and Control Research and Technology
    Symposium (ICCRTS 2005), Washington DC, USA

72
References (3)
  • Grant, T.J. 2005b. Unifying Planning Control
    with an OODA-based Architecture. In Proceedings,
    South African Institute of Computer Scientists
    Information Technologists (SAICSIT 2005), White
    River, RSA
  • Habermas, J. 1979. Communication and the
    Evolution of Society. Beacon Press, Toronto,
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