decision making, decision support & problem solving

@MartinSpecken#CognitiveEngineering

Decision-making models, decision support, and problem solving

Mark R. Lehto, Fiona Fui-Hoon Nah, Ji Soo Yiin Human Factors Fundamentals (2012)


Integrative model of decision making

• Single DM• Time pressure• Multiple stages• Risk attitudes• Knowledge• Decision tools• Multiple DMs


(Sometimes overlapping)

1. Group

2. Dynamic

3. Routine

4. Conflict

Categories of decision making (1/5)

@MartinSpecken#CognitiveEngineeringGroup decision making

•Debate•Bargain•Vote


@MartinSpecken#CognitiveEngineeringDynamic decision making

• Decision 1: Take medical test• Decision 2: What to do with the result?


@MartinSpecken#CognitiveEngineeringRoutine decision making


@MartinSpecken#CognitiveEngineeringConflict-driven decision making


Various forms of conflict must be resolved beforean alternative action can be chosen.


Decision making models (1/3)

1. Normative

2. Behavioral

3. Naturalistic


Normative decision models (1/6)

Classic decision theory with 4 elements:

• Potential actions to choose between [A]

• Events/world states [E]

• Probabilities [P] from combination [A] & [E]

• Consequences [C] from combination [A] & [E]



1. Dominance

2. Maximizing expected value

3. Subjective expected utility theory

4. Multiattribute utility theory

@MartinSpecken#CognitiveEngineering Dominance

Occurs between two alternativeactions, Ai and Aj , when:

Action Ai is at least as good as Aj

– for all events EAND

– for at least one event Ek

then Ai is preferred to Aj


@MartinSpecken#CognitiveEngineeringMaximizing Expected Value

Select the alternative with the greatest expected value.

• 3 kittens are stuck in trees• Decision:

– Save 3 kittens is 3 timesas good as saving 1 kitten.

• Choises:– 100% chance to save 1 kitten

Expected value = 1 * 1 = 1– 50% chance to save all 3 kittens + 50% to save 0 kittens

Expected value = ( 3 * 0,5 + 0 * 0,5 ) = 1,5


@MartinSpecken#CognitiveEngineeringSubjective Expected Utility Theory

Basic axioms (Dutch: grondstelling) of rational choise:

• If A > B and B > C , then A > C

• People’s preferences can conflict with the axioms.• Movement toward less restrictive standards.


@MartinSpecken#CognitiveEngineeringMultiattribute Utility Theory


Consider attractiveness of• Economic benifits• Social benefits• Environmental benefits



1. Normative

2. Behavioral

3. Naturalistic


Behavioral decision models (1/5)

Normative decision models don’t always work when compared to human behavior.

1. Statistical estimation and inference

2. Preference and choise

3. Adaptive decision behavior

4. Behavior economics

@MartinSpecken#CognitiveEngineeringStatistical estimation and inference

1960s: People behave as ’intuïtive statisticians’. Many examples of findings in the paper. A selection:

• DMs tend to ignore the reliability of the evidence.

• DMs tend to seek out confirming evidence rather than disconfirming evidence.

• DMs are overconfident in their predictions.

Behavior decision models (2/5)

@MartinSpecken#CognitiveEngineeringPreference and choise

People’s preferences changewhen the outcomes areframed in terms of costs,as opposed to benifits.


Research: observing human preference and choise and comparing it with the SEU theory

@MartinSpecken#CognitiveEngineeringAdaptive decision behavior


Individual DM uses different strategies

in different situations.

@MartinSpecken#CognitiveEngineering Behavior economics




1. Normative

2. Behavioral

3. Naturalistic


Naturalistic decision models (1/5)

In dynamic and realistic environment, actions by decision maker are made sequentially in time.

1. Levels of task performance

2. Recognition-primed decision making

3. Dominance structuring

4. Explanation-based decision making

@MartinSpecken#CognitiveEngineeringLevels of task performance

Most decisions are made on a routine basis. The levels of performance tasks are based on:

• Skills• Rules• Knowledge• Judgement


@MartinSpecken#CognitiveEngineeringRecognition-primed decision making

80% of firefighters make decisions based on some sort of situation recognition


@MartinSpecken#CognitiveEngineeringDominance structuring

Nonroutine decisionsinvolve sequence of:

1. Screen alternatives.2. Select alternative.3. Check dominance of selection to

other alternatives.4. No dominance? Restructure info

to force dominance.


@MartinSpecken#CognitiveEngineeringExplanation-based decision making

Jurors seem to organize massive amount of data in terms of stories describing cause and intent.



Group decision making (1/5)

1. Ethics and social norms

2. Group processes

3. Group performance and biasses

4. Prescriptive approaches

@MartinSpecken#CognitiveEngineeringEthics and social norms

Four dilemma’s of right versus right (Kidder, 1995)

1. Truth versus Loyalty

2. Individual versus Community

3. Short term versus Long term

4. Justice versus Mercy


@MartinSpecken#CognitiveEngineering Group processes

Tuckman (1965):

1. Forming (initial orientation)

2. Storming (conflict)

3. Norming (develop cohesion, express opinions)

4. Performing (obtain solutions)


@MartinSpecken#CognitiveEngineeringGroup performance and biasses

Strong opposition to usefull products


@MartinSpecken#CognitiveEngineeringPrescriptive approaches



1. Decision analysis

2. Individual decision support

3. Group and organizational decision support

4. Problem solving

Decision support and problem solving (1/5)

@MartinSpecken#CognitiveEngineering Decision analysis


C11

C12

C21

C22

E1

E2

E1

E2

A1

A2

P1

1 - P1

1 – P2

P2

A = ActionE = EventP = ProbabilityC = Consequenses

@MartinSpecken#CognitiveEngineeringIndividual decision support


@MartinSpecken#CognitiveEngineeringGroup and organizational decision support

Negotiation Support Systems assist people in activities that are competitive of involve conflicts of interest.


@MartinSpecken#CognitiveEngineering Problem solving

Psychologist work togetherwith computer scientist to

understand the human mind



Book Malcolm Cook et al. (2007)

http://tinyurl.com/boekdecisionmaking

http://tinyurl.com/boekdecisionmaking


Paper Sarah Sharples et al. (2007) (1/5)

http://www.ncbi.nlm.nih.gov/pubmed/17499573

http://www.ncbi.nlm.nih.gov/pubmed/17499573


Key components in airspace systems:

• Air traffic controllers

• Airline management

• Aircraft pilots

• Aircraft systems



Different goals:

• Air traffic controllerssafety of all the aircrafts in the system

• Airline managementexpediency & efficiency (profit)

• Aircraft pilotssafety & expediency of aircraft (local)



Different available information:

• Air traffic controllersmore: global traffic patternsless: global weather

• Airline managementless: traffic patternsmore: current weather



Increase of air traffic: How can extra aircrafts operate economically, efficiently and safe?

• Freeflightsome transfer of responsibility from air traffic controller to pilot for determining flight paths

• Datalinkprovide electronic exchange of information between pilots and air traffic controllers



Finally

The integrative model ofdecision making showshow the various approachesfit together as a whole.