12/7/2015 1 xx 2005-01-27 generic support for decision-making in effects-based management of...

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Generic Support forDecision-Making in

Effects-Based Managementof Operations

Defendant: KLAS WALLENIUS

Opponent: Prof. MIECZYSLAW M. KOKAR, Northeastern University, Boston

Defense of Doctoral ThesisJanuary 27, 2006

Klas Wallenius: Generic Support for Decision-Making in Effects-Based Management of Operations

Correction

p. 156

[Wallenius, 2004] Klas Wallenius. On support for situation awareness in command and control. In Proc. Seventh International Conference on Information Fusion (FUSION 2004), Stockholm Sweden, June 28 to July 1, 2004. In press.


Outline

• The PhD Project

• The work supported: Effects-Based Management of Operations

• Situation Awareness and Data Fusion

• DISCCO – Decision Support for Command and Control• The common situation model• Command support• Decision support

• Example Case: Riots at a Summit

• Conclusions and Further Work


The PhD Project• September 2000 – September 2005

• Performed• In Parallel and Scientific Computing

Institute• At School of Computer Science and

Communication, Royal Institute of Technology

• Sponsors• Vinnova• Saab Systems

• Supervisors• Prof. Stefan Arnborg, Nada• Prof. Berndt Brehmer, the Swedish

Defence Research Agency

• Involved in the work• Decision Support Group at Nada• DISCCO Project Group at Saab Systems• Contact Group at Saab Systems


Outline

• The PhD Project







Driving events: Berlin Wall, Estonia, World Trade Center, Madrid, Asia, Storm and Power Failure..

Change in threats New missions New technology

Background: Changed Threats in the

world


The Swedish Network-Based Defence

• No current threats to Swedish territory• Reduced number of forces• Methodology and technology transition• Cooperate with other organizations

• Based on ‘Network Centric Warfare’ and the ‘Revolution in Military Affairs’• Common Situation Awareness• Decision Superiority• Adaptable Organization• Precision Engagement

• It has been claimed that superior information will increase effects tremendously


People involved in management of

operations

• Military commanders and soldiers

• Rescue workers

• Incident commanders

• Police

• Crisis management

• Etc.


Time span of decision-making during long-term crisis preparation

Individuals withwearable equipment

Groups in mobile units

Crisis and operation management in staffs. Meeting context.

Long term planning in normal office environments.

Time for decision-making

Days

Hours

Seconds

Minutes

Months

Local Authorities

Municipalities

County Administrative Board

National Authorities

Government

Ministries

EU

UN


Time span of decision-making

during an upcoming crisis




Long term planning in normal office environments.


Days

Hours

Seconds

Minutes

Months

Local Authorities

Municipalities

County Administrative Board

National Authorities

Government

Ministries

EU

UN


Time span of decision-making during a military

operation




Large scale planning in normal office environments. Time for

decision-making

Days

Hours

Seconds

Minutes

Months

Small units

Larger units

Joint Headquarters

Battlegroup

Supreme Commander

Government

Ministry of Defence

EU

UN

Army, Air Force, and Naval Headquarters


A process for obtaining a desired strategic outcome on the enemy, through the synergistic, multiplicative, and cumulative application of the full range of military and non-military capabilities at the tactical, operational, and strategical levels.

US Joint Forces Command Glossary

Effects-Based Operations


Effects-Based Management of

Operations

• An interpretation from a decision-making perspective:• Make optimal use of available

resources to achieve effects according the task.

• The act of making decisions for subordinated resources regarding tasks and organization

• How to develop technical tools supporting this work?

• Both Civilian and Military Applications


EBO should consider effects beyond tactical

goals

• Facilitate the consideration of conflicting interests and goals in different dimensions• Human lives• Democratic rights• Infrastructure• Economy

• Main question: What if?

• Inherently uncertain – consider risks!


Decision-Making

• Prescriptive Theories• Decision Theory• Game Theory• Bayesian Approaches

• Descriptive Theories• Cognitive Psychology• Distributed Cognition• Naturalistic Decision-Making

(Klein, 1989)

• Military Decision-Making Methods• “Guide-Lines for Operational

Planning” (GOP)• “Bedömandemallen”• “Planning under Time Pressure”

(Thunholm, 2003)

EvolveTask

What?

EvolveSolutions

How?

PredictOutcome

Compare to

Task

MakeDecision


Outline

• The PhD Project







Artifacts to Improve Situation Awareness

Hugin and Munin ('thought' and 'memory') – Odin’s two ravens

Crystal Balls

Sauron’s Palantirs Galadriel’s Mirror

The Marauder’s Map The Chain Home Radar System


Data Fusion

Radar Infa Red Sensor

GPSESM

Data Fusion

Data Fusion is the process of combining data or information to estimate or predict entity states. Steinberg and Bowman 2001


Data Fusion: The Multi-Sensor Tracker


Type: F16

Data Fusion: The Multi-Sensor Tracker


Local Air Pictures


A Common Air Picture


Wide AreaNetwork

WCU

GlobalTracks

SuperiorLocal Tracks

SensorFusion

Presen-tation

WC

U WC

U

WCUWCU

WASP – The Wide Area Situation

Picture


Situation Awareness and the JDL Model

Situation Awareness

Level 1Perception of Elements in Current Situation


Level 2Comprehension

of Current Situation



Level 3Projection of

FutureStatus


FutureStatus

DecisionDecisionPerformance

of ActionsPerformance

of Actions

Goals & ObjectivesPreconceptions


Feedback

Data Fusion Domain

Level 1Object

Assessment

Level 1Object

Assessment

Level 2Situation

Assessment

Level 2Situation

Assessment

Level 3Impact

Assessment

Level 3Impact

Assessment

Level 0Sub-ObjectAssessment


Level 4Process

Refinement

Level 4Process

Refinement

Human/ComputerInterface


SourcesSources

DatabaseManagement

System

DatabaseManagement

System

• Mica Endsley (1985)

• Joint Directors of Laboratories


Situation Awareness and the JDL Model

Situation Awareness








FutureStatus


FutureStatus

DecisionDecisionPerformance

of ActionsPerformance

of Actions



Feedback

Data Fusion Domain

Level 1Object

Assessment

Level 1Object

Assessment

Level 2Situation

Assessment

Level 2Situation

Assessment

Level 3Impact

Assessment

Level 3Impact

Assessment



Level 4Process

Refinement

Level 4Process

Refinement



SourcesSources

DatabaseManagement

System

DatabaseManagement

System


Info on own andcollaborating forces

Info on other forces

L3: ProjectionPotential intentionsand their consequences

L2: RelationsVirtual objects, aggregation, organization

L1: Physical EntitiesSeparate objects

L0: ObservationsUninterpreted data

DISCCO Command Support andthe Common Situation Model

DISCCODecisionSupport

Sensors, Reconnaissance

Levels of Information and Tools Supporting Shared SA


Multi-Sensor Data Fusion

InformationFusion



Multi-Modal,Ubiquitous

and IntelligentUser Interfaces

L0: Reports

Techniques Supporting Situation Awareness

L1: ObjectsWASP

L2: RelationsCommonSituation

Model

L3: ProjectionInfluenceDiagramWhat If-Calculations

Human AssessmentsAgent-Based SimulationsExpert Systems

Situation AssessmentOntologies and Agent-Based Techniques

Multi-Sensor FusionMSTWASP Correlators

SensorsRadar, IR, GPS, …Human Reporters

Decision EvaluationHuman AssessmentsMulti-Attribute Utilities(Game Theory)


A Common Situation Model


Days

Hours

Seconds

Minutes

Months

L3: Projection

L2: Relations

L1: PhysicalResources

L0: Observations

The Common Situation Model


Outline

• The PhD Project







EvolveTask

TemplateGoals,

PreferenceFunction

EvolveSolutionsTemplate

Plans,Learning

Algorithms

PredictOutcomeSimulationModels,

War Gaming

Compare toTaskApply

PreferenceFunction

MakeDecision

Selectthe FittestSolution

EvolveTask

TemplateGoals,

PreferenceFunction


Plans,Learning

Algorithms

PredictOutcomeSimulationModels,

War Gaming

Compare toTaskApply

PreferenceFunction

MakeDecision


RoleRole 1

0..1

*

1

0..1

AssignedTasks

0..1

ApprovedPlan

PotentialPlans

*

SuperiorTask

ResourceResource

SuperiorResource

SubordinatedResource

*

**

*1

DefinedSubtasks

DefinedRoles

1*

SubordinatedRoles

SuperiorRoles

DefinedResources Responsible

Role

AffectingTasks

AffectedResources

AffectedTasks

AffectedPlans

*

**

1

1

**

AffectingTasks

AffectingTasks

DefiningPlan

DefiningPlan

DefiningPlan

Task TypeTask TypeCapability

Service

Type

1

*

*

*

*

*

*

Goals

Task

Goals

Task

Assessed Fulfillment

PlanAssessed Fulfillment

Plan

DISCCO – Decision Support for Command and

Control

• A Common Situation Model

• Command Support

• Decision Support


A Generic Approach

• Goals, tasks, resources, are relevant concepts, irrespective of managed domain

• Similar tools, methods, and info, across the dynamic organization

• Adaptable to specific tasks

• Facilitates flexible interoperability and cost-effective solutions

• Complementary to specialized applications • Open problem space• More time• From the human perspective


The Ontology: A Vocabulary for Describing Situations

Represents • The dynamic

networked based organization of resources, tasks and plans

• What is known of friendly and other forces

• From highest to lowest decision levels

Role 1

0..1

*

1

0..1

AssignedTasks

0..1

ApprovedPlan

PotentialPlans

*

SuperiorTask

Resource

SuperiorResource


*

**

*1

DefinedSubtasks

DefinedRoles

1*

SubordinatedRoles

SuperiorRoles


Role

AffectingTasks

AffectedResources

AffectedTasks

AffectedPlans

*

**

1

1

**

AffectingTasks

AffectingTasks

DefiningPlan

DefiningPlan

DefiningPlan

Task TypeCapability

Service

Type

1

*

*

*

*

*

*

Goals

Task


Plan

RoleRole 1

0..1

*

1

0..1

AssignedTasks

0..1

ApprovedPlan

PotentialPlans

*

SuperiorTask

ResourceResource

SuperiorResource


*

**

*1

DefinedSubtasks

DefinedRoles

1*

SubordinatedRoles

SuperiorRoles


Role

AffectingTasks

AffectedResources

AffectedTasks

AffectedPlans

*

**

1

1

**

AffectingTasks

AffectingTasks

DefiningPlan

DefiningPlan

DefiningPlan

Task TypeTask TypeCapability

Service

Type

1

*

*

*

*

*

*

Goals

Task

Goals

Task


PlanAssessed Fulfillment

Plan


An Example

Under OPCOM (Role)

Transport (Service)

Attack (Service)

101 Mech. Bn (Resource)

Transport (Capability)

Attack (Capability)

10 Mech. Bde(Resource)

Local Police(Resource)

Some Material(Resource)

Support With Transports (Role)

Transport (Service)

Transport (Task)


An Example

Under OPCOM (Role)

Transport (Service)

Attack (Service)

101 Mech. Bn (Resource)

Transport (Capability)

Attack (Capability)

10 Mech. Bde(Resource)

Local Police(Resource)

Some Material(Resource)

Support With Transports (Role)

Transport (Service)

Transport (Task)

GFOR Order of Battle (Plan)

10 BrigadeBattle Plan

(Plan)

Police’s CurrentDispatches (Plan)


Command Support

L3: Projection

L2: Relations


L0: Observations


L3: Projection

L2: Relations


L0: Observations


L3: Projection

L2: Relations


L0: Observations



Command SupportTools

• Support for navigating and maintaining the common model of the situation

• Provide support to describe and visualize problems and solutions in different views

• Once a solution (= a plan) is described it could be the subject for evaluation, as well as the baseline for an execution order

• Integrates planning and execution phases


Predicted Effects

Protect Meeting & VIPNo CasualtiesRight to DemonstrateCapture TroublemakersProtect Infrastructure

Ok Compromised SevereTopMeeting

Overall priorities

Legend

Outcome Probabilities

Peaceful Protesters (clusters of 100)

Troublemakers (clusters of 10)

Own Units

Important Object

VIP_1

VIP_2

Decision Support EvolveTask

TemplateGoals,

PreferenceFunction


Plans,Learning

Algorithms

PredictOutcomeSimulation

Models,War Gaming

Compare toTaskApply

PreferenceFunction

MakeDecision


EvolveTask

TemplateGoals,

PreferenceFunction


Plans,Learning

Algorithms


Models,War Gaming

Compare toTaskApply

PreferenceFunction

MakeDecision



Decision Support

Tools

• Enhance the human processto generate and evaluate solutions

• Support evaluation also during execution

• Gradual development of simulation and AI technology

EvolveTask

TemplateGoals,

PreferenceFunction


Plans,Learning

Algorithms


Models,War Gaming

Compare toTaskApply

PreferenceFunction,

Game Theory

MakeDecision


EvolveTask

TemplateGoals,

PreferenceFunction


Plans,Learning

Algorithms


Models,War Gaming

Compare toTaskApply

PreferenceFunction,

Game Theory

MakeDecision



Predicted Effects from Expert Systems

What ifExpert Systemor a Simulator

CombinationOf Actions

P(Effects)

P (Situation) P (Behavior)

• While the expert systems are domain specific, DISCCO may be kept general

• The results from the questions are stored in influence diagrams, maintaining a causal model between actions and effects


An ID represented in GENIE connected to the simulator


Going From a Chance Node to a ’Probabar’

OK (Casualties = 0)

Compromised (0 < Casualties ≤ 100)

Severe (100 ≤ Casualties)

52 %

38 %

10 %

Goal: No Casualties

Goal: No Casualties


Outline

• The PhD Project







Example Problem:Riots at a Summit

• Peaceful demonstrations and protests at a summit that degenerate into riots

• The security operation is managed by the police or by the military

• Protecting the right to demonstrate, human lives, the security of the top meeting, and private property, impose conflicting goals

• Psychological and social reactions must be considered


DISCCO


Ok Compromised SevereSummit

Overall priorities

Legend


Peaceful Demonstrants

Troublemakers

Own Units

Protected Object

VIP_1

VIP_2


DISCCO



Overall priorities

Legend



Troublemakers

Own Units

Protected Object

VIP_1

VIP_2

EscortSeparateBlock RoadReconnaissance

EscortSeparateBlock RoadReconnaissance


DISCCO



Overall priorities

Legend



Troublemakers

Own Units

Protected Object

VIP_1

VIP_2

Send Instructions


DISCCO



Overall priorities

Legend



Troublemakers

Own Units

Protected Object

VIP_1

VIP_2


Example of an Embedded Agent-Based Simulator


An ID represented in GENIE connected to the simulator


Outline

• The PhD Project







DISCCO: Scope and Solved Problems

• Support a higher order situation awareness, including• Own, hostile, allied and hostile units, important objects• Available capabilities• Assigned and assumed tasks and intents, organization• Monitoring and predicting effects and risks

• Facilitate fast planning and re-planning on the fly• ”What if” - design a plan and predict its effects• Issuing orders based on the plan• Reorganize in real time

• Enable collaboration between command levels and among peers

• Admit reuse of software and skills between different positions and activities


Currently Investigated Cases


Days

Hours

Minutes

Months

Tactical Command:Establish Surveillance

Tactical Command:Riot ControlSeconds

Joint Forces Command:Planning for NBC Defence


A roadmap for thedevelopment of DISCCO

Support for describing situation, tasks.Issuing orders

Dependent actions, uncertain information

Evaluation andmonitoring of plans through all phases

Support for gene-rating excellentplans

Bayesian networksand game theory

Situation model: ontology and distributed database

Integration with other services

CommandSupport (Methodologyand HMI)

Learning Algorithms

DecisionSupport(Technology)

Situation pictureGIS

Information Fusion

Security Authentication

Embedded agent-based simulation

GraphicalPlanning

PlanEvaluation

PlanGeneration

RiskAssessment


Continued Efforts

• Research• ROMEO – Research on

Management of Effective Operations

• Industrial Development• Work on DISCCO

• Hopefully this thesis provides a solid baseline for this work


Main Contributions in the Thesis

• A definition of ’Effects-Based Managament of Operations’

• The WASP approach to maintain a common situation picture

• The common situation model• A classification of the contents and tools to maintain

it• A definition of information quality• A generic ontology

• Examples of command support to manually maintain the model

• Examples of decision support to predict effects of actions• Use of monte carlo simulation and influence

diagrams• A preference function• Visualisation of effects in accordance to the task

• Three case studies


PublishedMaterial

• [Arnborg et. al. 2000] Stefan Arnborg, Henrik Artman, Joel Brynielsson, and Klas Wallenius. Information Awareness in Command and Control: Precision, Quality, Utility. In Proceedings Third International Conference on Information Fusion (FUSION 2000), pp. ThB1/25–32, Paris, July 2000.

• [Wallenius, 2000] Klas Wallenius. A Network Centric Info-Structure for the Swedish Armed Forces. In Milinf 2000, Enköping, Sweden, 2000.

• [Wallenius, 2000a] Klas Wallenius. Use of Modern Information Technology: WASP - A Common View of the Situation. In Technet Europe, 21st AFCEA Europe Symposium & Exposition, Prague, the Czech Republic, 2000.

• [Bergman and Wallenius, 2001] Niclas Bergman and Klas Wallenius. Providing the Common View of the Situation – the WASP Approach. In Information Management Challenges in Achieving Coalition Interoperability, Quebec City, Canada, May 29-30, 2001.

• [Brynielsson and Wallenius, 2001] Joel Brynielsson and Klas Wallenius. Game Environment for Command and Control Operations (GECCO). In Proceedings of the First International Workshop on Cognitive Research With Microworlds, pages 85–95, Granada, Spain, November 2001.

• [Brynielsson and Wallenius, 2003] Joel Brynielsson and Klas Wallenius. A Toolbox for Multi-Attribute Decision-Making. Technical Report TRITA-NA-0307, Department of Numerical Analysis and Computer Science, Royal Institute of Technology, 2003.

• [Huang et al., 2003] Qi Huang, Jenny Hållmats, Klas Wallenius, and Joel Brynielsson. Simulation-Based Decision Support for Command and Control in Joint Operations. In European Simulation Interoperability Workshop 2003, 03E-SIW-091, pages 591-599, Stockholm, Sweden, June 16-19, 2003.

• [Wallenius, 2002] Klas Wallenius. A Generic Model of Management and Command and Control. In Proceedings of 7th International Command and Control Research and Technology Symposium, Loews Le Concorde Hotel, Quebec City, QC, Canada, September 16-20, 2002.

• [Wallenius, 2003] Klas Wallenius. DISCCO – Decision Support for Command and Control. In CIMI 2003. Enköping Sweden, May 20-22, 2003.

• [Wallenius, 2004] Klas Wallenius. Support for situation awareness in command and control. In Per Svensson and Johan Schubert, editors, Proceedings of the Seventh International Conference on Information Fusion (FUSION 2004), Stockholm Sweden, June 28 to July 1, 2004.

• [Wallenius, 2004a] Klas Wallenius. DISCCO: Generic Support for C2 and Decision-Making. In Proceedings of 2004 Command and Control Research and Technology Symposium, San Diego, California, June 15-17.

• [Wallenius, 2004b] Klas Wallenius. Generic Support for Decision-Making in Management and Command and Control. Licentiate thesis, Department of Numerical Analysis and Computer Science, Royal Institute of Technology, Stockholm, Sweden, May 2004.

• [Wallenius, 2005] Klas Wallenius. Decision Support for Effects-Based Operations. In Proceedings of Second International Conference on Military Technology. Stockholm, Sweden, October 25-26, 2005.

• [Suzic and Wallenius, 2005] Robert Suzić and Klas Wallenius. Effects Based Decision Support for Riot Control: Employing Influence Diagrams and Embedded Simulation. In proceedings of MILCOM 2005, Atlantic City, NJ, October 17-20, 2005.

12/7/2015 1 xx 2005-01-27 generic support for decision-making in effects-based management of...

Documents

generic support

operation management

decisionmaking perspective

normal office environments

mobile unitscrisis

wearable equipmentgroups

meeting context

military operationindividuals