command decision-making with conflicting objectives: an exploration of some experimental data...
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Command decision-making with conflicting objectives: an exploration of some experimental data
Lorraine Dodd, Jim Moffat, Graham Mathieson, Jim Smith
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Main aim
To take our command decision models from beingessentially data-driven algorithms towards beingcontext-sensitive, information-driven agents so thatwe can capture, and to some extent decompose,effects of sharing information and interactions with others who may have conflicting objectives.
3Simple Pattern Matching for Course of Action selection
Sensor-derivedenemystrength
Own strength
Current CoA(e.g. attack)
AlternativeCoA(e.g. defend)
Estimate at time t
Covariance (entropy) at time t +1
Change at time t+1
4Status of rapid planning model for command agents
Sensor-derivedenemystrength
Own strength
Fixed doctrinalboundaries
imposed at allcommand levels
No hysteresisdue to uncertainty
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yt
t, t, t
Likelihood of yt
Pattern Classifierk pre-defined patterns
Patternpriors
Maximum likelihoodpattern for the data yt
(each pattern associated with a planned Course of Action)
Hassituationchanged
significantly?
k(t)
yes
t= t+1
no
Dynamic “smoother”
Belief inoutcome
Con-sequeceof getting it wrong.
CoA
DATA IN
DECISION OUT
Rapid planningalgorithm
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NOW
Means?
Penaltyfor gettingit wrong
Outcome projectiongiven decision/actions
Projection
Situation assessment
Desiredend-state
How is the penalty function changing with time?Anticipated different and conflicting end-state(s)?
WAY (CoA)
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Loss spaceSituation state space
Information Experience
Personality
Current state – probability dist’n
Choice/ activation of dimensions
Current loss dist’n
Decision
Action
?Activation of dimensions
Where am I?
How certain am I?
Consider expert knowledge. Can we assume it exists as patterns on a canonical set of state dimensions?
Is the assessment of loss (according to goals/ constraints and personal preference) essentially what determines how these patterns are accessed?
Is the loss function dependent on these patterns – as well as goals/ constraints and personality?
If so, then the product of the state and loss functions is where the simultaneous ‘pattern matching’ and ‘action selection’ occur.
We may be able to ‘recognise’ a pattern but may not select the associated response due to conflicts in loss assessments
Goals, weights
and limits
?
Assessment of loss – but how?
8Main objectives of the experiment• Single point decision gaming to investigate the impact of:
– changes in information quality on military command decisions
– personal attributes on decisions
• Direct elicitation of constructs to identify:
– indicators that serve as a basis for command decisions
– implications of variability for the rapid planning model
• RPD game - extra evening “entertainment”
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RPD experimental games
• War-fighting scenario
– Battle-group command decision for an armoured (3,0) BG in a delay/disrupt mission.
• Peace-support scenario
– similar level of command but decision concerning small armed units protecting a UN convoy at an IVCP
Twenty four brave participants (Maj and Lt Col)
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Customs Post
Protected enclave
Var
HQ location
??Probable LOAF LOAF
I
A 1 LI
0 5
N
Nettoyer PassI(-)
...
I
II
1 LI
I
B 1 LI
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Land rover sending radio message to HQ
UN aid Convoy
.(+)
Nettoyer Pass (as at 1530 hours)
N
10005002500
escort land rover
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Threat assessment
• Show of presence
• Provocation
• Theft of kit/convoy supplies
• Kidnap hostages
• Serious militia force (could escalate)
• All the above are possibilities
• Ambush set-up by LOAF
Risk assessment•Lack of info•Bimodal threat•Unpredictability•NATO aims•What’s at stake?
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Selected courses of action
• Negotiate
• Ask the terrorists what they want
• Request recce assets for more information
• Prepare forces (e.g. move artillery into range)
• Deploy QRF (covertly / overtly)
• Withdraw convoy to safe distance
• Defensive deployment / target LOAF
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Situation Assessment: Simplified
Threat Assessment
Magnitude ofpotential loss of life
largesmall
Posturing only
Criminaltheft
Hostagetaking
Militiaforce
LOAFAmbush
Do NOT Deploy
Negotiate
More info
What do they want?
Be recklessor
Do nothing
Employ QRF
Deploy QRF
Prepare
Deploy &Negotiate
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Terrorist threat
Magnitude of potential loss of life(convoy and own force protection)
Vectors showparticipants’ projectionsof situation
assessments
D
MQ
C
I HV
K
WU
AJ
XEB
S
G
F
R T
DeployQRF
Negotiatedo NOT deploy QRF
Prepare, talk,& inform police
prepareMorerecce
N
LO P Do both
ShowProvocation
SeriousEscalation
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No. of armed
men
Lethalityof wpns
Natureof IVCP
Locationof IVCP
Vulnerabilityof civilians
240 Neutralised
Potent
Calm
Agitated
clear
In pass
safe
danger
Threat assessment
Riskassessment
CoA
Outcomeprojections
Comfort zones(competance &controllability)
criticality
predictability Hopes, beliefs & expectations
NATO aim
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Negotiate Prepare Deploy Employ
Subjective assessment of CoAs
d0
tacticallevel
campaignlevel
Degree of Force
dT dC
OK
NOTOK
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Conclusions
• Experimental results appear to support rapid planning premise of recognition-primed decision-making
• Rapid planning model now with extended algorithm to handle C2 conflicting objectives through expected outcome
• This is not a model of human decision-making - it is a simplified representation for high-level OA models
• Decomposition of CIS Info, Experience and Personality is tricky
• Many important factors are not represented:
– Personal experience, history and training
– Individual preferences and biases
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Recommendations
• Need more experimental data
• Need to extend into dynamic patterns (e.g. AAWOs)
• Need to validate against exercises
• Implications for NEC and modelling of sharing
• Implications for CIS
• Implications for effects-based operations
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Dassel
EinbeckMarkoldendorf
Ilme
Ellensen
Odagssen
Luthorst
Elfas
Ahlsburg
II
I
II
I
I(-)II
II
II
I...
II
I
I
II
...
......
......
I II
I
I
.
II
II
I
I I
I
II
..
.
.. 2/179 TkII
2/179 MR
UKXX
GE
As at: 2115 hours
War-fighting scenario
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“It is general practice to deliberate upon affairs of weight when drunk. Then on the morrow when sober, the decision reached the night before is re-addressed. If it is approved of by all, they act on it. Sometimes however, if they happen to be sober at the first deliberation, they always reconsider the matter under the influence of wine”
tele: + 44 (0)1684 896135
Herodotus on the wise habits of the Persians, 500 BC
23War-fighting scenario
Dassel
EinbeckMarkoldendorf
Ilme
Ellensen
Odagssen
Luthorst
Elfas
Ahlsburg
III
II
I
I(-)
II
II
II
I...
I
I
I
I
II
...
......
......
I II
I
I
.
II
II
I
I I
I
I
I
..
.
..
2/179 TkII
2/179 MR
UKXX
GE
As at: 2117 hours
?
?
?
?
24Routes through Situation Assessment
Brigade Mission
Considered Not considered
Enemy dispositionCurrent +projected
Currentonly
unclear
Own assetsBest use to achieve mission Use to attack
local threat
clear
Preserve assets
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Situation assessments
• Enemy committing to axis/axes
• Enemy link-up to secure gap
• Enemy by-passing/leapfrogging my position
• Enemy blocking to isolate/fix me
• Encirclement/envelopment of my position
• Unclear on axis - could be feint
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Selected courses of action
• Attack armoured units to North
• Attack descant units in West
• Use of Arty to support/prepare attacks
• Move East to secure safe route out
• Stay in hides and do nothing
• Request information and more recce
• (Report situation and defer to Brigade)
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Theatre and life are made up of the unbrokenconflict between impressions and judgments -illusion and disillusion cohabit painfully and areinseparable.
Peter Brook Introduction to Marat/Sade
by Peter Weiss
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NOW
Means?
Penaltyfor gettingit wrong
Outcome projectiongiven decision/actions
Projection
Situation assessment
Desiredend-state
WAY (CoA)
Re-adjustsituationattributes
Lots of scope for causing effects…. But ...What effect will NEC have on C2 decisions?
29Route to situationassessment
•covariance/info entropy•consistency of data•confidence in sources•completeness
Riskanalysis
Situationassessment
CIS information &Intelligence
Experience Personality
Projection
•training•operational
Situationawareness
Threat assessment
backgroundknowledge
Command & Ops team
Mission Command priorities
“Comfort zones”
Operational context & history