<!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Archiving and Interchange DTD v1.0 20120330//EN" "JATS-archivearticle1.dtd">
<article xmlns:xlink="http://www.w3.org/1999/xlink">
  <front>
    <journal-meta />
    <article-meta>
      <title-group>
        <article-title>SmartSim: Improving visualization on social simulation for an emergency evacuation scenario</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>Antonio M. Diaz</string-name>
          <email>antoniom.diaz.dom@gmail.com</email>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Alvaro Carrera Oscar Araque</string-name>
          <email>a.carrera@dit.upm.es</email>
          <email>oscar.aiborra@alumnos.upm.es</email>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Carlos A. Iglesias</string-name>
        </contrib>
      </contrib-group>
      <pub-date>
        <year>2008</year>
      </pub-date>
      <fpage>151</fpage>
      <lpage>158</lpage>
      <abstract>
        <p>The simulation of indoor evacuation is important for rescue and safety management, while a better visualization of simulation could help users to understand the evacuation plan better and to design the evacuation activities more effectively. The purpose of this paper is to show an indoor evacuation simulator with more realistic graphical user interface for both interacting and visualizing the simulation of evacuation plans. The proposed evacuation simulator combines a social simulation framework UbikSim and a character animation platform SmartBody. UbikSim is used as a back-end social simulation engine for evacuation scene management and evacuation simulation calculation such as computing agent positions and evacuation path. SmartBody is focused on various behaviours and capabilities of agents with digital 3D character in real time, which is used to visualize the locomotion, emotion and facial expressions of agents with more realistic animations in simulation. We develop a connector for SmartBody to control and visualize the simulation by communicating with UbikSim. The proposed evacuation simulator is validated in a real world university evacuation scenario with multiple simulation settings.</p>
      </abstract>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>-</title>
      <p>
        Social simulation is a research field that applies computational
methods to study issues in the social sciences. In social simulation,
computers aim to imitate human reasoning activities by executing
processes, mechanisms and behaviours that build the reality. This
approach enables to investigate some complex models that cannot be
investigated through mathematical models. Social simulation is
considered as a third way of doing science, differing from both the
deductive and inductive approach [
        <xref ref-type="bibr" rid="ref1">1</xref>
        ], in which simulating a
phenomenon is akin to constructing artificial societies. Agent-Based
Simulation (ABS) is a kind of social simulation that represents a
simulation system as a society of agents that are designed to
describe the behaviour of observed social entities such as individuals or
groups [
        <xref ref-type="bibr" rid="ref6">6</xref>
        ]. Agent based social simulation is very useful to predict the
behaviour of individual agents or crowds in complex environments,
especially for simulating a dangerous environment and
experimenting the possible results of some actions based on simple rules.
      </p>
      <p>
        Various emergence cases can happen in a building such as fire,
earthquake, water leak, and gas leak, to name a few. Crowd
evacuations, such as disasters at massive parties, sport events and terrorist
attacks can also lead to tragedies when performed without careful
planning. In both type of emergencies, effective emergency
evacuation is a key component of emergency response. Emergency
evacuation preparation activities are required to be developed in advance
because they ensure that people can get to safety in case of emergency.
However, the evacuation demonstration in case of emergency is not
always feasible because of ethical, practical and financial issues [
        <xref ref-type="bibr" rid="ref8">8</xref>
        ].
In order to define effective evacuation plans, understanding disasters
and crowd emergency evacuation behaviours [
        <xref ref-type="bibr" rid="ref3">3</xref>
        ] conveniently with
low cost, the ABS can be used to simulate the crowd behaviour and
to analyze the effectiveness of evacuation plan. For instance, in a
evacuation simulator, the building is modeled and populated by
different numbers of agents representing various types of persons (e.g.,
handicapped persons, etc.) and common emergence situations such
as blocked doors. Different agents behaviour according to predefined
rules and the results of their actions are measured, hence the best of
evacuation model can be selected according to simulation, without
risking any real assets and situating human in dangerous situations.
      </p>
      <p>
        UbikSim 2.0 [
        <xref ref-type="bibr" rid="ref11">11</xref>
        ] is such kind of agent-based social simulator to
recreate the human behaviour inside a building. Specifically,
UbikSim is used to model the map of the building where the emergency
simulation takes place. Then, it simulates the virtual users (agents)
under emergency and calculates the evacuation path for agents based
on various criteria such as least crowd or nearest exit. However,
UbikSim has limited features of graphical user interface in
controlling and visualizing agents with abundant behaviours and various
characters, where agents are represented as simple as equivalent
figures in the map and there is no way to inspect visually the agents
types (e.g. man or woman) or their emotions (e.g. fear or happiness).
In order to enhance the visualization of UbikSim framework, we
propose to incorporate SmartBody [
        <xref ref-type="bibr" rid="ref12">12</xref>
        ] to provide visualization of
agents in an animation approach. More specifically, the agents in the
map are represented as human-like 3D animations. The movements
of agents can be demonstrated in a more realistic way and with more
options such as walk, run or jump. Furthermore, agents are able to
express emotions in their animated face and to response to events in an
interactive life-like manner such as speak with gestures and face
expressions. Moreover, the description of such behaviour is simplified
by using Behavior Markup Language (BML) [
        <xref ref-type="bibr" rid="ref9">9</xref>
        ] because SmartBody
is also a BML realization engine that transforms BML behaviour
descriptions into real time animations. Consequently, the proposed
system can provide a complete graphic rendering platform to bring
various characters with predefined movement animations and behaviour
sets together with a social simulation engine. In this way, we could
add many different type of agents by simply adding their behaviour
descriptions through BML settings. In addition, the system is also
designed to be easily extended for future development.
      </p>
      <p>To summarize, we would like to show the main contributions of
this work:</p>
      <p>We propose and implement a novel agent-based evacuation
simulator, named SmartSim2, that combines an agent-based social
simulator UbikSim with a character animation platform SmartBody.
The proposed evacuation simulator has been validated and
demonstrated in a realistic school building with different simulation
scenarios.</p>
      <p>The rest of this paper is organized as follows. In section 2, we
present the background of this work. Section 3 gives the overview of
the proposed evacuation simulator and discusses the implementation
details. Finally, we describe the evaluation of the proposed simulator
in a school evacuation scenario with different settings in Section 4
and close the paper in Section 5 by showing the main conclusions of
this work and providing a possible view on future work.
2</p>
    </sec>
    <sec id="sec-2">
      <title>Background</title>
      <p>This section introduces some background knowledge of required
components to develop the proposed evacuation simulator. We first
review the idea and functionality of agent-based social simulator
UbikSim in Section 2.1. Then, we introduce the character animation
platform SmartBody and the behaviour description language BML in
Section 2.2.
2.1</p>
    </sec>
    <sec id="sec-3">
      <title>Agent-based Social Simulator UbikSim</title>
      <p>
        Agent-based social simulation [
        <xref ref-type="bibr" rid="ref5">5</xref>
        ] is good at predicting the behaviour
of agents in complex environments. Ubiksim 2.0 [
        <xref ref-type="bibr" rid="ref11">11</xref>
        ] is an
implementation of an agent-based social simulator which has been
developed by Universidad de Murcia and Universidad Polite´cnica de
Madrid 3. It is a framework that can be used to develop social
simulation which emphasizes the construction of realistic indoor
environments, the modeling of realistic human behaviours and the evaluation
of Ubiquitous Computing and Ambient Intelligence systems.
UbikSim is implemented in Java and employs a number of third-party
libraries such as SweetHome3D and MASON. It consists of a console
used to launch the simulation as well as a map in 3D or 2D where the
position of all the agents involved in the simulation can be visualized.
      </p>
      <p>
        Moreover, UbikSim tries to be a tool for using Multi-Agent Based
Simulation (MABS) [
        <xref ref-type="bibr" rid="ref4">4</xref>
        ] in Ambient Intelligence (AmI) [
        <xref ref-type="bibr" rid="ref10">10</xref>
        ] which
is a computerized environment that is sensitive to human and objects
actions. MABS consists of modeling the environments with many
artificial agents in order to observe the behaviours of agents, while
it is possible to learn about their reactions. In case of evacuation
simulation, effective activities can be derived from observing the
behaviours of artificial agents and the outcomes of some simulated
phenomena in evacuation. These behaviours cannot be observed in
nonevacuation conditions. In contrast, other kinds of simulations model
the entire environment as mathematical models where the
individuals are viewed as a structure that can be characterized by a number of
variables. Conventionally, it is not feasible to test a large number of
users in AmI, whereas UbikSim enables the simulation of social
behaviours from large group of users by applying the MABS approach
to AmI environments.
      </p>
      <p>As an example, Figure 1 illustrates a map used for evaluation
based on UbikSim, including a demostration of an agent-based
simulation.</p>
      <sec id="sec-3-1">
        <title>2 SmartSim Repository: https://github.com/gsi-upm/SmartSim 3 Ubiksim Public Repository: https://github.com/emilioserra/UbikSim</title>
        <p>
          SmartBody framework4 is an open source character animation
platform for animating Embodied Conversational Agents (ECAs) [
          <xref ref-type="bibr" rid="ref12">12</xref>
          ],
which provides capabilities for digital 3D characters in real time such
as the animations of locomotion, steering, object manipulation, lip
syncing, gazing, non-verbal behaviour or re-targeting. SmartBody
contains its own viewer and 3D renderer so that it can be run as a
standalone system or incorporated into game or simulation engines.
SmartBody is focused on proving various behaviours and interactive
characters of artificial agents so we use it as graphical user interface
of evacuation simulator, while UbikSim takes charge of scene
management and simulation computation. In addition, the life-like
behaviour requires the synchronized movement of multiple parts of the
agents simulated body. For example, to realize the gaze behaviour
requires coordination of eye, head, neck movements. Moreover, to
support coherent interpretation of behaviour, the animation of gestures,
eye flashes and speech audio must be synchronized in time with each
other. SmartBody implements the behaviour realization engine that
transforms BML behaviour descriptions into real time animations.
As a consequence, we are able to have various predefined animations
of agents with different types by describing their different behaviours
with BML.
        </p>
        <p>Listing 1. A BML Example
&lt;bml i d = ” bml1 ” c h a r a c t e r I d = ” R a c h e l ”&gt;
&lt; r e q u i r e d&gt;
&lt;g a z e i d = ” g a z e 1 ” t a r g e t = ”PERSON1” /&gt;
&lt;s p e e c h i d = ” s p e e c h 1 ”&gt;</p>
        <p>&lt; t e x t&gt;Welcome&lt; / t e x t&gt;
&lt; / s p e e c h&gt;
&lt; / r e q u i r e d&gt;
&lt;h e a d i d = ” nod1 ” t y p e = ”NOD” /&gt;
&lt; / bml&gt;</p>
        <p>
          BML is an XML based description language for controlling the
verbal and non verbal behaviour of ECAs [
          <xref ref-type="bibr" rid="ref2">2</xref>
          ]. BML is used to
describe the physical realization of behaviours (e.g. speech and gesture)
of the agents expressing them with movements that need to be
realized by an agent. Those movements are single elements (e.g. gaze,
        </p>
      </sec>
      <sec id="sec-3-2">
        <title>4 SmartBody Web Site: http://smartbody.ict.usc.edu/</title>
        <p>speech, head) and listed one after another, as exemplified in
Listing 1.
3</p>
      </sec>
    </sec>
    <sec id="sec-4">
      <title>SmartSim Simulator</title>
      <p>The main goal of the proposed evacuation simulator is to use
UbikSim as social simulation engine and to use SmartBody as graphical
interface of the simulator. This section presents the implementation
details of the proposed simulator system in Section 3.1 and also
offers an overview of the simulation gateway in Section 3.2.
3.1</p>
    </sec>
    <sec id="sec-5">
      <title>Architecture Overview</title>
      <p>The SmartSim simulator system consists of a social simulation
module (UbikSim), a simulation gateway module and a graphical
visualization module (SmartBody). The overview of the proposed system
has been illustrated in Figure 2. The idea is to connect the social
simulation engine with the animation engine through the simulation
gateway, in order to provide an integrated evacuation simulation
system. We rely on the existing simulation engine, while we develop
the simulation gateway and incorporate the animation engine into a
complete graphical user interface for controlling, managing and
visualizing the simulation.</p>
      <p>The social simulation module is based on UbikSim and is used
for managing agents, describing the emergency scenario, modeling
the indoor evacuation environment and creating evacuation plan. The
graphical visualization module is based on SmartBody and is used
for visualizing the agent behaviour in life-like animation in
simulation. To combine UbikSim and SmartBody, we implement a
simulation gateway that helps to manage the social simulation configuration
and to provide communication between UbikSim and SmartBody in
real time while running the simulation. Moreover, a user friendly
graphical user interface based on SmartBody has been implemented
to utilized the simulation gateway so that end users can manage and
visualize the simulation conveniently.</p>
      <p>In addition, UbikSim provides a scene editor that can pass the
environment map to SmartBody. As SmartBody is not able to
perform the simulation and calculate the paths that agents have to
follow in order to evacuate the building. It relies on UbikSim to perform
simulation computation and retrieves position data from UbikSim in
real time. Within the map, and position data in run time, SmartBody
presents a realistic 3D evacuation environment and enables users to
control the simulation such as pausing or advancing.</p>
      <p>
        UbikSim has many kinds of options, such as editing and
creating artificial environment with an easy to use interface,
configuring various number of agents. The communication between UbikSim
and SmartBody is based on Representational State Transfer
(RESTful) [
        <xref ref-type="bibr" rid="ref7">7</xref>
        ] architecture through web requests.
3.2
      </p>
    </sec>
    <sec id="sec-6">
      <title>Simulation Gateway Implementation</title>
      <p>The simulation gateway is composed by four different modules:
simulation configuration module, graphical visualization module, real
time communication module and simulation control module. The
simulation configuration module parses user defined configuration
of simulation such as agent numbers, emergency scenarios, initial
positions and evacuation plans. Some relevant configuration options
are illustrated in Table 1. Then, the configuration data are passed to
UbikSim social simulator through web request API and to
SmartBody through its Python API. According to the configuration data,
social simulator initializes the simulation, creating the agents and
setting their positions. The scenario resources are loaded to set the
mark for emergency such as emergency position. The character
resources such as skeleton and polygonal model are loaded for further
usage of SmartBody.</p>
      <p>Option
amountAgents
amountLeaders
ubikSimServer
meshScenario
modeSimulation</p>
      <p>Description
The number of agents in our simulation.</p>
      <p>The number of leaders in our simulation.</p>
      <p>The address of UbikSim server.</p>
      <p>The scenario file for simulation.</p>
      <p>The possible simulation modes.</p>
      <p>Based on configuration data, SmartBody creates the simulation
scene (e.g. maps and agents) and starts the graphical visualization
module that calls the graphic interface of SmartBody and a default
camera to display the simulation. Moreover, the configuration
module also loads the description resources for different character of
agents from BML description resources, so the different type of
animation can be rendered in simulation.</p>
      <p>Option
output=web
control=pause
control=play
control=stop
control=frames
position=people
position=map
position=emergency
position=(id,x,y)</p>
      <p>Effect
Displays the web graphic interface.</p>
      <p>Executes the pause control.</p>
      <p>Executes the play control.</p>
      <p>Executes the stop control.</p>
      <p>Starts the displayers in the server side.</p>
      <p>Returns the agents positions.</p>
      <p>Returns the map coordinates and obstacles.</p>
      <p>Returns the emergency position and room.</p>
      <p>Adds the agent to the position.</p>
      <p>The real time communication module retrieves agents’ positions
and paths from UbikSim and converts them into specific form of
position and path for SmartBody. Consequently, the SmartBody can
present the animation of agents that execute the evacuation plan. The
UbikSim simulation run time Web API is illustrated in Table 2.</p>
      <p>Furthermore, a simulation control module is implemented in
SmartBody to control the simulation and make agents follow their
path. It can be used to control every step of simulation and make
agents Pause, Advance, and Stop. The actions of those commands are
passed to UbikSim through the real-time communication module, so
the gateway is able to coordinate the simulation in real time between
UbikSim and SmartBody. After simulation finished, the simulation
control module will record the simulation results containing the time
that an agent spent to exit the building from its initial position and
more relevant data for further analysis.
4</p>
    </sec>
    <sec id="sec-7">
      <title>Use case scenarios</title>
      <p>The implemented evacuation simulator system has been validated
in a real use case scenario which is simulating evacuation
activities. The indoor environment is selected as the building B of the
School of Telecommunication Engineers (ETSIT) of the
Universidad Polite´cnica de Madrid. A demonstration video of all the
validation tasks can be found in YouTube5. The implementation of the
simulator as well as validation case studies are published and
available in a public Github repository6. We will first introduce how we
create the validation map in Section 4.1 and then present three
evacuation scenarios. Section 4.2 illustrates a single agent scenario where
an agent escapes, leaving the building from any initial position of the
building. Also, this section presents a more complicated case where
multiple agents evacuate the building following a agent leader.
Finally, we present a more realistic social simulation that different type
of agents escape the building from different initial position and adopt
different evacuation path.
4.1</p>
    </sec>
    <sec id="sec-8">
      <title>Map Creation</title>
      <p>The map of the building has been modeled in UbikSim and is
illustrated in Figure 1. The generated map file has been exported to
SmartBody in configuration. Note that any polygonal model
generated with 3D modeling program such as Blender could fit the
requirement of SmartBody. UbikSim editor is based on SweetHome3D
which is a free indoor design application. We can draw the map of
our scenario, arrange furniture on it and visualize the results in 3D.
It is also easy to create a scenario as drawing the walls and rooms.
Several objects libraries have been added and can be imported to
the editor, which can add completion and detail of our scenario. We
implemented an extension in UbikSim, so the created scene can be
exported to SmartBody automatically. Figure 3 shows the 3D school
map in SmartBody GUI that have been passed from UbikSim, using
the map shown in Figure 1.
4.2</p>
    </sec>
    <sec id="sec-9">
      <title>Single Agent Escaping</title>
      <p>As mentioned previously, the simulation of agents is based on
UbikSim, while SmartBody retrieves the paths and positions from it. By
configuring scene in the UbikSim editor, we set the positions and
numbers of agents, scenarios and location of the emergency. All these
data is passed to SmartBody via the simulation gateway. UbikSim
also retrieves the initial configuration from simulation gateway. The
5 SmartSim Video: https://www.youtube.com/watch?v=8kGKD8Ofxuw
6 SmartSim Repository: https://github.com/gsi-upm/SmartSim
simulation result data are also generated by simulation gateway
containing the exit time of each agent. We first validate the system in
a scenario of evacuation of single agent from the building. Agent
will escape the building following the path given by UbikSim. We
demonstrate the emergency and the character escaping the building.
The configuration of simulation is set as single agent without any
character. The agent needs to exit the building from his initial
position based on the predefined path. SmartBody is set up to show the
evacuation of agent with animations, while simulation gateway will
record the time the agent used to escape the building. This scenario
is used to validate the system correctness.</p>
      <p>The second scenario is the extension from the previous one by
adding the number of agents and a simple evacuation model. The
escaping in a crowd is a common phenomena in evacuation and is the
main place that dangerous situation may appear. In the crowd
simulation, we design a number of agents and one of these agents become
the leader, while the other agents will follow the leader from their
initial point to the exit. This scenario helps to extend the previous
scenario with consideration of multiple agents.</p>
      <p>It is a common phenomena in evacuation plans some crowds are
leaded by a leader. The setting is similar to the previous case, while
we also define the numbers of leaders and their following groups
of agents. The non-leader agents will follow the path as their
assigned leader. After simulation, the exit time of all the agents will
be recorded. Figure 4 shows the animation of crowd escaping with
leaders in SmartBody GUI. This scenario can help validate the
performance of simulator with multiple agents and validate the
correctness of evacuation plan execution.
4.3</p>
    </sec>
    <sec id="sec-10">
      <title>Social Simulation with Characters and</title>
    </sec>
    <sec id="sec-11">
      <title>Emotions</title>
      <p>Finally, we set a more realistic simulation scenario, where multiple
agents with different type of characters escaping the building from
different initial position following different paths. Figure 5 shows the
screenshot of animation of agents starting from different location and
execute different evacuation plans. It has been shown in Figure 5 that
the simulator is able to present the social simulation of emergency
evacuation correctly. Moreover, the visualization of the simulation
become more realistic because there more kind of agents with
different emotions. The previous scenario has leader and follower
characters, while the agents can have different gender or ages. For example,
Figure 6 illustrates a female agent named Rachel which is different
from the previous male agents. The SmartBody and BML enable the
animation of agents in a life-like way. By defining the behaviours in
BML files, agents can have different motions and face expression to
represent more human-like behaviours. For example, Figure 7
illustrates the agent expressing his happiness. This is achieved by
configuring the face element in BML and realized by SmartBody. We
believe that enabling the agents to express their feelings in face such
as fear in facing an emergency and happiness after evacuation can
make the visualization of simulation more realistic and help to make
the evacuation plans better.
5</p>
    </sec>
    <sec id="sec-12">
      <title>Conclusions and Future Works</title>
      <p>This paper presents an agent-based simulation system, named
SmartSim, for evacuations based on Ubiksim, where the graphical interface
has been enhanced with realistic animations and emotions in agents
using SmartBody.</p>
      <p>The interaction between UbikSim and SmartBody, which allowed
end-users to interact with simulation systems conveniently and
visualize the simulation more powerfully, is implemented in different
modules written in Python. The system is designed as modular
components that can ease the future implementation of various
simulation purposes. The system has provided facilities for creating
simulation scenarios easily based on simple configuration file and those
scenarios can be exported to UbikSim and SmartBody automatically.
The visualization of simulation is achieved by very detailed
artificial agents in animations. Furthermore, agents are able to express
emotions and various behaviours which make our simulator more
realistic. End users are allowed to select the numbers of agents as well
as their types with particular animation and behaviours.</p>
      <p>Several research lines that can be considered as following work to
continue and extend the features of this work. Firstly, a graphical
interface for scene control might be useful to help users in avoiding
mistakes in defining agent commands. Secondly, although
SmartBody offers very good performance of visualizing agent’s
animations, it can be integrated with a graphical engine such as Unity
to improve the quality of animation. Finally, apart from the current
desktop version, we are planning to implement a mobile version or
web-base version.</p>
    </sec>
    <sec id="sec-13">
      <title>ACKNOWLEDGEMENTS</title>
      <p>This work is supported by the Spanish Ministry of Economy and
Competitiveness under the R&amp;D projects SEMOLA
(TEC201568284-R) and MOSI-AGIL-CM (grant P2013/ICE-3019, co-funded
by EU Structural Funds FSE and FEDER).</p>
    </sec>
  </body>
  <back>
    <ref-list>
      <ref id="ref1">
        <mixed-citation>
          [1]
          <string-name>
            <given-names>Robert</given-names>
            <surname>Axelrod</surname>
          </string-name>
          , '
          <article-title>Advancing the art of simulation in the social sciences'</article-title>
          ,
          <source>Japanese Journal for Management Information System</source>
          ,
          <volume>12</volume>
          (
          <issue>3</issue>
          ), (
          <year>2003</year>
          ).
        </mixed-citation>
      </ref>
      <ref id="ref2">
        <mixed-citation>
          [2]
          <string-name>
            <given-names>Justine</given-names>
            <surname>Cassell</surname>
          </string-name>
          ,
          <article-title>Embodied conversational agents</article-title>
          , MIT press,
          <year>2000</year>
          .
        </mixed-citation>
      </ref>
      <ref id="ref3">
        <mixed-citation>
          [3]
          <string-name>
            <given-names>W</given-names>
            <surname>Challenger</surname>
          </string-name>
          ,
          <article-title>WC Clegg, and AM Robinson, 'Understanding crowd behaviours: Guidance and lessons identified'</article-title>
          ,
          <source>UK Cabinet Office</source>
          , (
          <year>2009</year>
          ).
        </mixed-citation>
      </ref>
      <ref id="ref4">
        <mixed-citation>
          [4]
          <string-name>
            <given-names>Paul</given-names>
            <surname>Davidsson</surname>
          </string-name>
          ,
          <article-title>'Multi agent based simulation: beyond social simulation'</article-title>
          ,
          <source>in Multi-Agent-Based Simulation</source>
          ,
          <fpage>97</fpage>
          -
          <lpage>107</lpage>
          , Springer, (
          <year>2000</year>
          ).
        </mixed-citation>
      </ref>
      <ref id="ref5">
        <mixed-citation>
          [5]
          <string-name>
            <given-names>Paul</given-names>
            <surname>Davidsson</surname>
          </string-name>
          , '
          <source>Multi agent based simulation: Beyond socialsimulation'</source>
          , (
          <year>2000</year>
          ).
        </mixed-citation>
      </ref>
      <ref id="ref6">
        <mixed-citation>
          [6]
          <string-name>
            <given-names>Paul</given-names>
            <surname>Davidsson</surname>
          </string-name>
          , '
          <article-title>Agent based social simulation: A computer science view'</article-title>
          ,
          <source>Journal of artificial societies and social simulation</source>
          ,
          <volume>5</volume>
          (
          <issue>1</issue>
          ), (
          <year>2002</year>
          ).
        </mixed-citation>
      </ref>
      <ref id="ref7">
        <mixed-citation>
          [7]
          <string-name>
            <given-names>Roy</given-names>
            <surname>Thomas</surname>
          </string-name>
          <string-name>
            <surname>Fielding</surname>
          </string-name>
          ,
          <article-title>Architectural styles and the design of networkbased software architectures</article-title>
          ,
          <source>Ph.D. dissertation</source>
          , University of California, Irvine,
          <year>2000</year>
          .
        </mixed-citation>
      </ref>
      <ref id="ref8">
        <mixed-citation>
          [8]
          <string-name>
            <given-names>Steve</given-names>
            <surname>Gwynne</surname>
          </string-name>
          , ER Galea,
          <string-name>
            <given-names>M Owen</given-names>
            ,
            <surname>Peter J Lawrence</surname>
          </string-name>
          , and L Filippidis,
          <article-title>'A review of the methodologies used in the computer simulation of evacuation from the built environment', Building and</article-title>
          environment,
          <volume>34</volume>
          (
          <issue>6</issue>
          ),
          <fpage>741</fpage>
          -
          <lpage>749</lpage>
          , (
          <year>1999</year>
          ).
        </mixed-citation>
      </ref>
      <ref id="ref9">
        <mixed-citation>
          [9]
          <string-name>
            <given-names>Stefan</given-names>
            <surname>Kopp</surname>
          </string-name>
          , Brigitte Krenn, Stacy Marsella,
          <string-name>
            <given-names>Andrew N.</given-names>
            <surname>Marshall</surname>
          </string-name>
          , Catherine Pelachaud, Hannes Pirker,
          <string-name>
            <surname>Kristinn R. Thrisson</surname>
          </string-name>
          , and Hannes Vilhjlmsson4, '
          <article-title>Towards a common framework for multimodal generation: The behavior markup language'</article-title>
          , (
          <year>2006</year>
          ).
        </mixed-citation>
      </ref>
      <ref id="ref10">
        <mixed-citation>
          [10]
          <string-name>
            <given-names>Emilio</given-names>
            <surname>Serrano</surname>
          </string-name>
          and Juan Botia, '
          <article-title>Validating ambient intelligence based ubiquitous computing systems by means of artificial societies'</article-title>
          ,
          <source>Information Sciences</source>
          ,
          <volume>222</volume>
          (
          <issue>0</issue>
          ),
          <fpage>3</fpage>
          -
          <lpage>24</lpage>
          , (
          <year>2013</year>
          ).
          <article-title>Including Special Section on New Trends in Ambient Intelligence and Bio-inspired Systems</article-title>
          .
        </mixed-citation>
      </ref>
      <ref id="ref11">
        <mixed-citation>
          [11]
          <string-name>
            <surname>Emilio</surname>
            <given-names>Serrano</given-names>
          </string-name>
          , Geovanny Poveda, and Mercedes Garijo, '
          <article-title>Towards a holistic framework for the evaluation of emergency plans in indoor environments'</article-title>
          , Sensors,
          <volume>14</volume>
          (
          <issue>3</issue>
          ),
          <fpage>4513</fpage>
          -
          <lpage>4535</lpage>
          , (
          <year>2014</year>
          ).
        </mixed-citation>
      </ref>
      <ref id="ref12">
        <mixed-citation>
          [12]
          <string-name>
            <surname>Marcus</surname>
            <given-names>Thiebaux</given-names>
          </string-name>
          , Stacy Marsella,
          <string-name>
            <given-names>Andrew N.</given-names>
            <surname>Marshall</surname>
          </string-name>
          , and Marcelo Kallmann, 'Smartbody:
          <article-title>Behavior realization for embodied conversational agents'</article-title>
          ,
          <source>in Proceedings of the 7th International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 1</source>
          , AAMAS
        </mixed-citation>
      </ref>
    </ref-list>
  </back>
</article>