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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

A Multi-Agent System for Visualization Simulated User Behaviour

B. de Vries, J. Dijkstra


Agenda
Agenda Behaviour

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 Behaviour

  • Traditional process and use

  • Envisioned process and use


Traditional process sketch
Traditional process: Sketch Behaviour

  • Paper & Pencil

  • Reflection on Thoughts

  • Vague


Traditional process design
Traditional process: Design Behaviour

  • 2D/3D Modeling

  • Material use

  • Consultancy: Installation, Construction, etc.


Traditional process presentation
Traditional process: Presentation Behaviour

  • Convey design

  • Impression of building


Envisioned process 3d modeling
Envisioned process: 3D Modeling Behaviour

  • Direct manipulation

  • Implicit relations

  • Sculpturing


Envisioned process scene painting
Envisioned process: Scene Painting Behaviour

  • Realistic images

  • No construction material


Envisioned process evaluation
Envisioned process: Evaluation Behaviour

  • Indoor climate

  • Lighting

  • Structural behavior

  • Acoustics

  • User behavior





  • 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


Essentials of Cellular Automata problem to assess how their design or planning decisions will affect the behavior of individuals.


Cellular automata are characterized by the following features:

  • Grid

  • Time

  • Cell

  • State


Cellular automata model of traffic flow
Cellular Automata Model of Traffic Flow behavior is completely specified in terms of a local relation


Agent Characteristics behavior is completely specified in terms of a local relation


Agent definitions
Agent Definitions behavior is completely specified in terms of a local relation

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 behavior is completely specified in terms of a local relation

  • 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 behavior is completely specified in terms of a local relation

State

Perception

Action

Sensors

Effectors

Production

System


Multi agent simulation models

Multi Agent Simulation Models behavior is completely specified in terms of a local relation


Offers the promise of behavior is completely specified in terms of a local relationsimulating 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 behavior is completely specified in terms of a local relation


Artificial Intelligence behavior is completely specified in terms of a local relation

Cellular

Automata

Distributed

Artificial

Intelligence

Multi Agent Simulation Models


Motivation
Motivation behavior is completely specified in terms of a local relation

  • 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 behavior is completely specified in terms of a local relation

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


Different neighborhoods
different neighborhoods behavior is completely specified in terms of a local relation


Transition of a state of a cell
transition of a state of a cell behavior is completely specified in terms of a local relation


Agent model
Agent Model behavior is completely specified in terms of a local relation


User agent
User Agent behavior is completely specified in terms of a local relation

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





Simulation experiment
Simulation Experiment Technology

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 ...


Demo Technology


Conclusions

Conclusions 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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