A multi agent system for visualization simulated user behaviour
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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. VR Technology in (Architectural) Design. Traditional process and use Envisioned process and use.

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A Multi-Agent System for Visualization Simulated User Behaviour

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A multi agent system for visualization simulated user behaviour

A Multi-Agent System for Visualization Simulated User Behaviour

B. de Vries, J. Dijkstra


Agenda

Agenda

VR-DIS research programme:

B. de Vries

AI for visualization of human behavior:

J. Dijkstra


Vr technology in architectural design

VR Technology in (Architectural) Design

  • Traditional process and use

  • Envisioned process and use


Traditional process sketch

Traditional process: Sketch

  • Paper & Pencil

  • Reflection on Thoughts

  • Vague


Traditional process design

Traditional process: Design

  • 2D/3D Modeling

  • Material use

  • Consultancy: Installation, Construction, etc.


Traditional process presentation

Traditional process: Presentation

  • Convey design

  • Impression of building


Envisioned process 3d modeling

Envisioned process: 3D Modeling

  • Direct manipulation

  • Implicit relations

  • Sculpturing


Envisioned process scene painting

Envisioned process: Scene Painting

  • Realistic images

  • No construction material


Envisioned process evaluation

Envisioned process: Evaluation

  • Indoor climate

  • Lighting

  • Structural behavior

  • Acoustics

  • User behavior


Example urban plan

Example: Urban plan


Towards a multi agent system for visualizing simulated user behavior

Towards a Multi-Agent System for Visualizing Simulated User Behavior


A multi agent system for visualization simulated user behaviour

Introduction of the Model


A multi agent system for visualization simulated user behaviour

  • 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


A multi agent system for visualization simulated user behaviour

Essentials of Cellular Automata


A multi agent system for visualization simulated user behaviour

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

Cellular automata are characterized by the following features:

  • Grid

  • Time

  • Cell

  • State


Cellular automata model of traffic flow

Cellular Automata Model of Traffic Flow


A multi agent system for visualization simulated user behaviour

Agent Characteristics


Agent definitions

Agent 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).


Agent properties

Agent 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


Agent architecture

Agent Architecture

State

Perception

Action

Sensors

Effectors

Production

System


Multi agent simulation models

Multi Agent Simulation Models


A multi agent system for visualization simulated user behaviour

Offers the promise of simulating 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


Towards the framework

Towards the Framework


A multi agent system for visualization simulated user behaviour

Artificial Intelligence

Cellular

Automata

Distributed

Artificial

Intelligence

Multi Agent Simulation Models


Motivation

Motivation

  • 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.


Network model

Network Model

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


Different neighborhoods

different neighborhoods


Transition of a state of a cell

transition of a state of a cell


Agent model

Agent Model


User agent

User Agent

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

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

  • Sscenario , 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


The integration of cellular automata and multi agent technology

The Integration of Cellular Automata and Multi Agent Technology

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

  • a network-based view

  • a main node-based view

  • an actor-based view


Network grid and decision points

network grid and decision points


Main node based view

main node-based view


Actor based view network based view

actor-based view / network-based view


Simulation experiment

Simulation 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 ...


A multi agent system for visualization simulated user behaviour

Demo


Conclusions

Conclusions


A multi agent system for visualization simulated user behaviour

  • 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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