A DESCRIPTION METHOD FOR MULTI-AGENT
SIMULATION MODEL UTILIZING TYPICAL ACTION
PATTERNS OF AGENTS
Taiki Enomoto, Gou Hatakeyama, Masanori Akiyoshi and Norihisa Komoda
Osaka University, Yamadaoka 2-1, Suita, Osaka 565-0871, Japan
Keywords:
Multi agent simulation, Description of events, Typical action patterns, Event flow.
Abstract:
Recently, there are various proposals on tool for multi-agent simulation. However, in such simulation tools,
analysts who do not have programming skill spend a lot of time to develop programs because notation of sim-
ulation models is not defined sufficiently and programming language is varied on tools. To solve this problem,
a programming environment that defines the notation of simulation model based on graph representation is
proposed. However, in this environment, we still need to write programs about a ow of event and contents
of agents’ action and effect. So, we propose a description method for multi-agent simulation model utilizing
typical action patterns of agents. In this method, users write about designs of contents of event based on typical
action patterns which are “interrogative (4W1H) and verbs”, and designs of a flow of event. In this paper, we
executed experiments that compare time needed for examinees to generate programs by a conventional method
and our programming environment. Experimental result shows the time to generate programs by utilizing our
programming environment less than that by utilizing a conventional one.
1 INTRODUCTION
Recently, multi-agent simulation (MAS) is expected
to be effective for simulation of complex system
such as biology, ecosystem, social system and eco-
nomics(MacNealy, 1999)(Axelrod, 1995). MAS is a
method of simulation that includes some autonomous
agents which act in spontaneous manners like a hu-
man and make interactions each other. The purpose
of MAS is to analyse phenomenon generated by in-
teractions of agents. Agents make action based on
rules and affect other agents.
MAS system consists of these local rules. There
have been some studies of MAS, and various MAS
tools have been developed (Swarm(Minar et al.,
1996), Repast(North et al., 2005), artisoc(kke)) and
used for many simulationDHowever,analysts spend a
lot of time to describe a simulation model of the prob-
lem, because there is no way of understandable nota-
tion of simulation models based on feature of MAS.
Moreover, when analysts write the program codes of
simulation, they have to use specific programming
language of MAS tool which makes them spend a lot
of time to acquire programming skills.
To solve the above-mentioned problems, a pro-
gramming environment that defines the notation of
simulation model based on graph representation is
proposed(Hatakeyama et al., 2007). However, in this
environment, we still need to write program codes
about a flow of event and contents of agents’ action
and effect.
In this paper, we propose a description method
for multi-agent simulation model utilizing typical ac-
tion patterns of agents. In this method, users write
about contents of event based on typical action pat-
terns, which are “interrogative (4W1H) and verbs”,
and designs of a flow of an event.
2 A MULTI-AGENT SIMULATION
PROGRAMMING
ENVIRONMENT
2.1 Outline of Programming
Environment
Analysts who run simulation roughly sketch interac-
tions of objects in simulation, and they design a simu-
lation model by embody their understanding. Next,
316
Enomoto T., Hatakeyama G., Akiyoshi M. and Komoda N. (2008).
A DESCRIPTION METHOD FOR MULTI-AGENT SIMULATION MODEL UTILIZING TYPICAL ACTION PATTERNS OF AGENTS.
In Proceedings of the Third International Conference on Software and Data Technologies - ISDM/ABF, pages 316-319
DOI: 10.5220/0001900303160319
Copyright
c
SciTePress
Figure 1: Outline of programming environment.
they write program codes based on the simulation
model and run simulation with MAS tools. We can
use several MAS tools as execution platforms, but
these tools do not support to describe a simulation
model and develop programs. To solve these prob-
lems, a programmingenvironment that defines the no-
tation of simulation model based on graph represen-
tation is proposed(Hatakeyama et al., 2007).
Figure 1 shows overall configuration of our simu-
lation programming environment. First, analysts de-
scribe a simulation model of target problem by utiliz-
ing the editor for MAS model. Secondly, this sim-
ulation model is transformed into XML (eXtensible
Markup Language) to represent information of the
simulation model. This XML data is interpreted and
transformed into a simulation program code by the
program generater. We use “artisoc” as MAS execu-
tion platform. With MAS execution platform, we run
the generated simulation program code and get simu-
lation results.
2.2 MAS Model Editor
In our simulation programming environment,we need
some elements to define the model of a target prob-
lem. Figure 2 shows these elements and a descrip-
tion of model based on these elements. In this ex-
ample, the relationship between shops and consumers
is shown in the upper part of Figure 2. First, we
have to describe an agent itself and interaction of each
“agent” such as consumers and shops. An agent has
“attributes” which represent an agent’s state. Also, an
agent has “action” which influences other agents be-
havior or attributes. We need these 3 elements to de-
scribe a simulation model. Then the simulation model
based on graph representation is depicted in the lower
part of Figure 2. An agent’s attribute is represented
as “variable node”, an agent’s action is represented as
“event” and an effect is represented as “arc”.
An agent’s attributes, action and effect are repre-
sented as a node, an event and an arc in MAS model
respectively. However, contents of action and transi-
tions of event are not represented well. So, we pro-
pose a description method for multi-agent simulation
model utilizing typical action patterns of agents to
support users to describe such events.
Figure 2: A description method of model.
3 EVENT DESCRIPTION
3.1 Outline of Event Description
Contents of events that agents behave independently
are able to be described by utilizing “when” (when a
condition is satisfied), “who” (an agent), “how” (fol-
lowing the rule), “what” (object) and “verb” (do).
In this paper, we define “interrogative (4W1H) and
verbs” as typical action patterns of agents and pro-
pose a description method for multi-agent simulation
model utilizing typical action patterns of agents.
In addition to use of the interrogative (4W1H) and
verbs for expressing the contents of agent events, we
introduce “flow diagram of event transitions” for ex-
pressing interactions between agents.
3.2 Design of Event Contents
Figure 3 shows outline of design of event contents.
We prepare pull-down choice lists to design event
contents about “interrogative (4W1H) and verbs”. In
case of designing event that is selection of shop and
if we want to design such as “if distance between a
customer and a shop is within a certain value that we
decide in advance, the customer selects the shop.”, we
describe a model such as “When => Always”, “Who
=> customer”, “How => Min (Distance (customer,
shop))”, “What => shop” and “Verb => Select One”.
A DESCRIPTION METHOD FOR MULTI-AGENT SIMULATION MODEL UTILIZING TYPICAL ACTION
PATTERNS OF AGENTS
317
Figure 3: Design of event contents.
Figure 4: Example of a flow of an event.
There is a problem that it is difficult to prepare
all verbs which are used whole entire world to design
event contents. So, in this paper, we defined vocabu-
lary of verbs by putting the verbs that we use everyday
together through the lens of the agent world.
3.3 Design of a Flow of an Event
Figure 4 shows a flow of an event. The transition of
an event is described about each agent in the flow of
an event. The condition of transition is described in
each arc by referring to the vocabulary that is stated
in section 3.2. Also, timing of firing the event and the
procedures that the event occurs are described in the
flow of the event. In the Figure 4, the state “wait” rep-
resents that one agent waits for other agents to com-
plete an event that it is necessary to be completed for
one agent to transit next event.
4 AUTOMATIC GENERATION OF
PROGRAMMING CODES
MAS model that is described by utilizing a model de-
scription method based on graph representation are
represented in a form of XML. Event contents that
are included in the MAS model and information of
transition of events are represented in the same form.
The XML file is input into the program generater and
Figure 5: Outline of automatic generation of programming
codes.
converted to program codes. Figure 5 shows the out-
line of automatic generation of programming codes.
Also, we use “artisoc” as an execution platform in
this paper. In “artisoc”, description of agents is made
up of “declaration of value that agents have”, “agents
rules that are executed per unit time” and “definition
of function by users”. In Figure 5, MAS model corre-
sponds with declaration of value, design of event flow
corresponds with agents rule and design of event con-
tents corresponds with definition of function.
5 EVALUATION
We evaluate our description method by executing ex-
periment on “shopping mall model”.
5.1 Generation of a Shopping Mall
Model
Figure 6 shows outline of a shopping mall.
Customers arrive at the west gate or the south gate
by some probability.
Customers move in the shopping mall freely.
Shop B passes coupons at the west gate and cus-
tomers receive them at a constant rate.
Customers go into the shop if distance between
customer and a shop is within a constant value.
Shops do not allow customers to go into the shop
when each store capacity is not sufficient. And
ICSOFT 2008 - International Conference on Software and Data Technologies
318
customers flounce in the shopping mall freely
again.
If customers in shop A have a coupon, they leave
the shop and do away with their coupon and they
flounce in the shopping mall freely again. In other
cases, customers buy goods.
When customers finish buying goods, they leave
the shopping mall
The shops count the number of their customers
Figure 6: Outline of shopping mall.
5.2 Generation of Model by Examinees
5.2.1 Precondition of Experiment
First, examinees receive an explanation about the
shopping mall model that is described in section 5.1.
Secondly, they generate the shopping mall model by
utilizing our event description method. Finally, we
compare required time, which examinees generate a
model by utilizing our approach and by writing raw
program codes for “artisoc”.
Two examinees have programming experience,
however they inexperienced in MAS or “artisoc”. So,
they learn how to use “artisoc” by reading its manual.
5.2.2 Result of Experiment
Table 1 shows the result of experiment.
Table 1: Result of experiment.
In experimental result, it is clarified that time,
which is required to generate a simulation model by
utilizing “artisoc”, is reduced by utilizing our event
description method. Additionally, our event descrip-
tion method is easy to use for not only person of ex-
perience but also amateur programmers of MAS.
However, simulation sometimes does not go well,
because users draw the model in wrong manners. For
example, in case of “leave shop event”, users have
to describe processing to reduce the number of cus-
tomers. However, because of a perceived notion that
the number of customers reduces naturally, users fail
to describe this procedure explicitly. So, this simula-
tion does not go well. We need to consider a method
to bridge the gaps between users’ perceived notions
and codes.
6 CONCLUSIONS
In this paper, we proposed a description method for
multi-agent simulation model utilizing typical action
patterns of agents in a programming environment that
defines the notation of simulation model based on
graph representation.
In this paper, we executed experiment and com-
pared required time, which examinees generate a
model by utilizing our approach and by “artisoc”. As
a result, it is clarified that time is reduced by utilizing
our event description method. Additionally, an event
description method that we propose is easy to use for
not only person of experience but also amateur pro-
grammers of MAS.
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A DESCRIPTION METHOD FOR MULTI-AGENT SIMULATION MODEL UTILIZING TYPICAL ACTION
PATTERNS OF AGENTS
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