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A Multi-Agent System for Visualization Simulated User Behaviour B. de Vries, J. Dijkstra.

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A Multi-Agent System for Visualization Simulated User Behaviour B. de Vries, J. Dijkstra
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Page 1: A Multi-Agent System for Visualization Simulated User Behaviour B. de Vries, J. Dijkstra.

A Multi-Agent System for Visualization Simulated

User Behaviour

B. de Vries, J. Dijkstra

Page 2: A Multi-Agent System for Visualization Simulated User Behaviour B. de Vries, J. Dijkstra.

Agenda

VR-DIS research programme:

B. de Vries

AI for visualization of human behavior:

J. Dijkstra

Page 3: A Multi-Agent System for Visualization Simulated User Behaviour B. de Vries, J. Dijkstra.

VR Technology in (Architectural) Design

• Traditional process and use

• Envisioned process and use

Page 4: A Multi-Agent System for Visualization Simulated User Behaviour B. de Vries, J. Dijkstra.

Traditional process: Sketch

• Paper & Pencil• Reflection on

Thoughts• Vague

Page 5: A Multi-Agent System for Visualization Simulated User Behaviour B. de Vries, J. Dijkstra.

Traditional process: Design

• 2D/3D Modeling• Material use• Consultancy:

Installation, Construction, etc.

Page 6: A Multi-Agent System for Visualization Simulated User Behaviour B. de Vries, J. Dijkstra.

Traditional process: Presentation

• Convey design• Impression of

building

Page 7: A Multi-Agent System for Visualization Simulated User Behaviour B. de Vries, J. Dijkstra.

Envisioned process: 3D Modeling

• Direct manipulation

• Implicit relations• Sculpturing

Page 8: A Multi-Agent System for Visualization Simulated User Behaviour B. de Vries, J. Dijkstra.

Envisioned process: Scene Painting

• Realistic images• No construction

material

Page 9: A Multi-Agent System for Visualization Simulated User Behaviour B. de Vries, J. Dijkstra.

Envisioned process: Evaluation

• Indoor climate• Lighting• Structural

behavior• Acoustics• User behavior

Page 10: A Multi-Agent System for Visualization Simulated User Behaviour B. de Vries, J. Dijkstra.

Example: Urban plan

Page 11: A Multi-Agent System for Visualization Simulated User Behaviour B. de Vries, J. Dijkstra.

Towards a Multi-Agent System for Visualizing Simulated User Behavior

Page 12: A Multi-Agent System for Visualization Simulated User Behaviour B. de Vries, J. Dijkstra.

Introduction of the Model

Page 13: A Multi-Agent System for Visualization Simulated User Behaviour B. de Vries, J. Dijkstra.

• Architects and urban planners are often faced with the problem to assess how their design or planning decisions will affect the behavior of individuals.

• One way of addressing this problem is the use of models simulating the navigation of users in buildings and urban environments.

A Multi-Agent System based on Cellular Automata

Page 14: A Multi-Agent System for Visualization Simulated User Behaviour B. de Vries, J. Dijkstra.

Essentials of Cellular Automata

Page 15: A Multi-Agent System for Visualization Simulated User Behaviour B. de Vries, J. Dijkstra.

Cellular automata are discrete dynamical Cellular automata are discrete dynamical systems whose behavior is completely systems whose behavior is completely specified in terms of a local relationspecified in terms of a local relation

• Cell

Cellular automata are characterized by the following features:

• Grid • State • Time

Page 16: A Multi-Agent System for Visualization Simulated User Behaviour B. de Vries, J. Dijkstra.

Cellular Automata Model of Cellular Automata Model of Traffic FlowTraffic Flow

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Agent Characteristics

Page 18: A Multi-Agent System for Visualization Simulated User Behaviour B. de Vries, J. Dijkstra.

Agent DefinitionsAgent Definitions

Agents are computational systems that inhibit some complex dynamic environment, sense and act autonomously in this environment, and by doing so realize a set of goals or tasks for which they are designed (Maes).

An autonomous agent is a system situated within and part of an environment that senses that environment and acts on it, over time, in pursuit of its own agenda (Franklin & Graesser).

Page 19: A Multi-Agent System for Visualization Simulated User Behaviour B. de Vries, J. Dijkstra.

Agent PropertiesAgent Properties• Autonomy

- agents have some control over their actions and internal state

• Social ability- agents interact with other agents

• Reactivity- agents perceive their environment and respond to

changes in it

• Pro-activeness- agents exhibit goal-directed behavior by acting on

their own initiative

• ? Mentalistic capabilities- knowledge, belief, intention, emotion

Page 20: A Multi-Agent System for Visualization Simulated User Behaviour B. de Vries, J. Dijkstra.

Agent ArchitectureAgent Architecture

State

ProductionSystem

ActionPerception

Sen

sors

Eff

ecto

rs

Page 21: A Multi-Agent System for Visualization Simulated User Behaviour B. de Vries, J. Dijkstra.

Multi Agent Simulation Models

Page 22: A Multi-Agent System for Visualization Simulated User Behaviour B. de Vries, J. Dijkstra.

Offers the promise of simulatingsimulating autonomous agents and the interaction between them.

behaviors evolve dynamically during the simulation

Evolution capabilities:

• evolution of the agent’s environment

• evolution of the agent’s behavior during the simulation

• anticipated behavior

• unplanned behavior

Page 23: A Multi-Agent System for Visualization Simulated User Behaviour B. de Vries, J. Dijkstra.

Towards the Framework

Page 24: A Multi-Agent System for Visualization Simulated User Behaviour B. de Vries, J. Dijkstra.

CellularAutomata

Artificial Intelligence

DistributedArtificial

Intelligence

Multi Agent Simulation Models

Page 25: A Multi-Agent System for Visualization Simulated User Behaviour B. de Vries, J. Dijkstra.

MotivationMotivation

• Develop a system how people move in a particular environment.• People are represented by agents.• The cellular automata model is used to simulate

their behavior across the network.

• A simulation system would allow the designer to assess how its design decisions influence user movement and hence performance indicators.

Page 26: A Multi-Agent System for Visualization Simulated User Behaviour B. de Vries, J. Dijkstra.

Network ModelNetwork Model

The network is the three-dimensional cellular automata model representation of a state at a certain time.

Page 27: A Multi-Agent System for Visualization Simulated User Behaviour B. de Vries, J. Dijkstra.

different neighborhoodsdifferent neighborhoods

von Neum ann

r = 1 r = 2

Moore

r = 1 r = 2

Page 28: A Multi-Agent System for Visualization Simulated User Behaviour B. de Vries, J. Dijkstra.

transition of a state of a celltransition of a state of a cell

Page 29: A Multi-Agent System for Visualization Simulated User Behaviour B. de Vries, J. Dijkstra.

Agent ModelAgent Model

ConjointMeasurement

Agent

DecisionSupportAgent

ActorAgent 1

ActorAgent n

SubjectAgent

Virtual EnvironmentSimulation Model

VirtualInteraction

Interface AgencyTechnical

Communication IntuitiveCommunication

Page 30: A Multi-Agent System for Visualization Simulated User Behaviour B. de Vries, J. Dijkstra.

User AgentUser Agent

Define an user-agent as: U = < R | S >, where:

• R is finite set of role identifiers; {actor, subject}

• S scenario , defined by: S = <B, I, A, F, T>, where:• B represents the behavior of user-agent i • I represents the intentions of a user-agent i • A represents the activity agenda user user-agent i • F represents the knowledge of information about

the environment, called Facets• T represents the time-budget each user-agent

possesses

Page 31: A Multi-Agent System for Visualization Simulated User Behaviour B. de Vries, J. Dijkstra.

The Integration of Cellular Automata The Integration of Cellular Automata and Multi Agent Technologyand Multi Agent Technology

• an actor-based view

Initially, we will realize different graphic representations of our simulation:

• a network-based view

• a main node-based view

Page 32: A Multi-Agent System for Visualization Simulated User Behaviour B. de Vries, J. Dijkstra.

network grid and decision pointsnetwork grid and decision points

main decision point

remaining walkway section decision point

section bound

E1 E2

E3

°

°

° ° °

°

° °

° S6

S7

S8S10 S9

°

°

°

S11

S12

S13

° ° ° S14S15S16

° ° ° ° ° S1 S2 S3 S4 S5

S18S17

S19 S20

Page 33: A Multi-Agent System for Visualization Simulated User Behaviour B. de Vries, J. Dijkstra.

main node-based viewmain node-based view

links

actual path

actual decision point

Page 34: A Multi-Agent System for Visualization Simulated User Behaviour B. de Vries, J. Dijkstra.

actor-based view / network-based viewactor-based view / network-based view

Page 35: A Multi-Agent System for Visualization Simulated User Behaviour B. de Vries, J. Dijkstra.

Simulation ExperimentSimulation Experiment

Design of a simulation experiment of pedestrian movement.

Considering a T-junction walkway where pedestrians will be randomly created at one of the entrances.

Some impressions ...

Page 36: A Multi-Agent System for Visualization Simulated User Behaviour B. de Vries, J. Dijkstra.
Page 37: A Multi-Agent System for Visualization Simulated User Behaviour B. de Vries, J. Dijkstra.
Page 38: A Multi-Agent System for Visualization Simulated User Behaviour B. de Vries, J. Dijkstra.
Page 39: A Multi-Agent System for Visualization Simulated User Behaviour B. de Vries, J. Dijkstra.

Demo

Page 40: A Multi-Agent System for Visualization Simulated User Behaviour B. de Vries, J. Dijkstra.

Conclusions

Page 41: A Multi-Agent System for Visualization Simulated User Behaviour B. de Vries, J. Dijkstra.

Complex behavior can be simulated by using the concept of cellular automata in the context of multi-agent technology.

The development of multi-agent models offers the promise of simulating autonomous individuals.

A multi-agent model can be used for visualizing simulated user behavior to support the assignment of design performance.

The proposed concept potentially has a lot to offer in architecture and urban planning when visual and active environments may impact user behavior and decision-making processes.


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