Gaming Simulation Dr.ir. Sebastiaan Meijer Associate professor, - - PowerPoint PPT Presentation

Dr.ir. Sebastiaan Meijer

Associate professor, Faculty of TPM, TU Delft

Gaming Simulation

Overview

• Systems thinking and its

actors

• Multi-actor, multi method
• What is Gaming Simulation
• Example: ProRail
• Example: SprintCity
• Future trends

System thinking and its actors

• Socio-technical systems
• Choices in governance, management

and operations

• Freedom of choice for travellers
• Complex adaptive systems
• Companies, operators =

Adaptive agents

• Intertwining & complexity =

Dynamic relations

• Performance = Emergent behaviour
• Research & Design tools:
• ften mono-disciplinary & disjoint

Social Network SociotechSoc Technical Network

Diagrams

Actor 4 Actor 1 Actor 2 Actor 3 Actor 5

Component 1 Component 2 Component 3 Component 4 Component 5 Human 1 Human 2 Human 3

Actor 6

Sociotechnical Network

Complex Adaptive System

Multi-actor, multi-method!

Engineers Design process (V-model, step-based approach) Cognitive uncertainty ‘Best’ solution, best available knowledge Hard tools: simulation, models, calculations Managers Control cycles (yearly, periodically) Performance (indicator) uncertainty ‘Accepted’ solution, reasonable knowledge Mixed tools: project and process management Politicians Fluid coalition forming (policy arenas) Scope (boundary) uncertainty ‘Negotiated’ solution, disputed knowledge Soft tools: participation, image, spinning

What is Gaming Simulation?

• A gaming simulation session:
• mimics the behaviour of a real-world

system

• Uses real people as decision makers
• Combines with (computerized)

simulation models

• A broad range of simulations in which

the role of a human decision maker is enacted by a real human participant instead of a computer.

• Technology is not essential, but

driven by the goals of the gaming simulation.

History of gaming simulation

• War games (19th and 20th century)
• Policy making: testing complex systems
• Richard D. Duke, 1974
• Gibbs, 1974
• Related to SSM (Checkland and Scholes)
• Shubik. The uses and methods of gaming.

Elsevier New York, 1975.

• Computer gaming: since 1980’s
• Serious applications: end of ’90’s

Now: integration of the two streams

Analytical science Gaming simulation design Roles Rules Objectives Constraints Load Situation

• Org. change evaluation

Design science Participants Learning eval. Participants with exp. Real world Qualitative Data Quantitative Data Session Organization Changed Organization

Example: ProRail

• ProRail is the Dutch railway

infrastructure manager

• Gaming simulation to reduce

uncertainty in decision making

• n operational future
• Four-year research contract,

working closely on some key projects.

• Computer-based & analog games
• Depends on phase in decision

making

Gaming in railway traffic control

• Traditional innovation in railway operations is top-

down

• Testing in computer simulations
• Then push to operations?
• But will it work in practice?
• Current robustness and resilience is already under pressure
• Engineering has many assumptions about the operations.
• The difference between theory and practice exists only in

practice

• Talking with operations doesn’t help: do it with

them!

• Reason is found in implicit, but very effective, mental

models

The challenge

• 100% extra trains 2020
• 50% in 2012 regional
• First: major corridors
• “Untimetabled traffic”
• Like a metro system
• All within 10% of the

budget required in the ‘old’ way

Project: ETMET 2010

• Real-world test:
• Sept 2010
• Amsterdam – Eindhoven
• 6 – 6 – 2 pattern
• Preparations Spring 2010
• Question: how to handle a

major disruption?

• Two types of handling predefined

by staff experts

• Will this work out with the operation?

ETMET Game

Models of reality

• Trains: scour sponges
• Combination of wagons of certain

type

• Each with associated capacity
• One train driver, one head of cabins

(flags with real numbers)

• A route-setting (real map)
• A time-table (card, real numbers)
• Real data sheets
• Video distribution for computer

systems

• Portophone for RailPhone / intercom

Model types

• ‘Iconic’ representation: relevant elements
• ‘As-if-real’ representation: crucial

elements

• ‘Playful’ representation: non-relevant

elements

Example: SprintCity

• Relation urban development &

transport system

• Deltametropool agency
• Urban inner city areas connected

through metro-like trains. Transport system constraints on urban planning

• Computer-based game
• For domain specialists
• Multi actor
• Fictitious or real roles

Example: SprintCity

Model-based evaluation

• Public transport mobility

versus urban profile

• Constraints on money, other

stations, transport capacity and environmental factors

• Equations behind purely

qualitative interface

• Learning outcomes: complexity

& dependency in urban

• development. Need for

collaboration with transport

Model-based evaluation

Future Vision

• Gaming, Simulation and Big Data will

integrate

• Multi-scale modelling, and data-driven gaming
• Visualisation and Interactivity Computing
• Technology becomes useful for gaming
• Decision-making evidence-based
• Joint fact finding
• Integration of operations in strategic

decisions

• Inductive and deductive cycles through gaming,

participatory methods, etc.

Gaming Simulation

Visualisation & Interactivity

Analogue Platforms

Big Data

Distributed Simulation

Cognitive Task analysis

Gaming Simulation

Visualisation & Interactivity

Analogue Platforms

Big Data

Distributed Simulation

Cognitive Task analysis

Gaming Simulation

Visualisation & Interactivity

Analogue Platforms

Big Data

Distributed Simulation

Cognitive Task analysis

Conclusions

• Designing

infrastructures is a multi-actor problem

• This requires methods

that involve people.

• Gaming simulation

Thanks for your attention!

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