TEACHING MULTI-AGENT SYSTEMS WITH THE HELP OF ARES: MOTIVATION AND MANUAL
Date
2002-11-07
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Abstract
In the last years, multi-agent systems (MAS) have become a very
active research area that has connections to many other areas, both inside and
outside of Computer Science. Consequently, courses about MAS are starting to
be developed and even the first text books are on the market (see [AL02] and
[Wo02]). Perhaps even more than in other areas of Computer Science, teaching
MAS has to involve practical experiences by the students. The interaction of
agents has many surprises (as has the interaction of human beings) and hands-on
experiences with issues like timing of actions to achieve cooperation,
communication and the effects of, changes in the surroundings, and so on, are
necessary to let students understand not only the basic problems but also why
certain concepts are the way they are. For getting practical experience with
developing multi-agent systems the students need an environment (or testbed) in
which their agents will interact, that sets the basic rules for the agents and
guards these rules against violations by the agents. There are already such
environments available, namely the environments used in various competitions,
as for example the RoboCup Simulation League Soccer Server ([seeKu02]) or the
TAC Game Servers of the Trading Agent Competition (see[W e+ 01]). But, for
teaching purposes, the goals for the development of these environments do not
totally agree with the goals we need for a teaching environment: having
successful systems available via WWW allows for a lot of cheating (resp.
requires a lot of work of the instructor spend on counter actions) and results
in students not making the experiences they are supposed to make. Also, the
two cited environments are rather specialized, so that certain experiences are
outside of their scope. There are a lot of other didactic reasons for not
using testbeds that were developed and are used to evaluate research systems,
as we will see later in this report. In this report, we present the ARES
system (Agent Rescue Emergency Simulator) that is intended to be a testbed for
multi-agent systems and to be used for teaching MAS. ARES follows the lead of
the RoboCup Rescue Initiative (see [RR02]) in choosing as the application
scenario rescuing survivors in a disaster zone. The basic tasks the students
have to include into the agents that form their multi-agent system that is
employed within ARES are locating survivors and removing rubble to reach and
rescue those survivors. ARES allows for many different variants of the basic
setting, by varying the information the agents have when starting, the cost of
communication, the methods for agents to regain energy, and so on. While many
basic requirements of acting in a real disaster scenario are touched,
nevertheless they are simplified within ARES towards a game-like scenario that
allows students, resp. student teams to develop agents tat act as team in ARES
in the 4 months a beginners course in MAS takes. This report is organized as
follows: After this introduction, we take a closer look at the requirements on
a testbed for MAS (resp. MAS concepts) that is aimed at helping in teaching
MAS basics. This then leads to stating our goals in developing ARES. In
Section 3, we present the system using two different views: the view of a
student using it and the view of an instructor configuring ARES for his/her
course (and we will also provide some information about the implementation of
ARES). In Section 4, we present observations we made when using ARES for
teaching MAS to a mixed class of graduate and undergraduate students at the
University of Calgary. Finally, we will conclude with some remarks on future
work. The report also contains as appendices descriptions of the actions ARES
allows agents and their syntax, of the graphical viewer that allows building
scenarios and observing a rescue team, of the installation requirements and
procedure, and of the parameters for defining the \world laws".
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Computer Science