Game Development Reference
In-Depth Information
Table 4. Results at the conclusion of the Game
for each Partner/s
These factors were taken from the random values
produced in an initial game run.
Player/s
Population
Bushels
Acres
Decision-Making
Human
57
3
45
Fuzzy Part-
ners
22
697
502
There are many methods by which decision-
making can be achieved. As part of the architec-
tural implementation, each process of the layered
collaborative architecture is designed to allow
replacement. Two techniques were applied to
Hammurabi's Boardroom: A fuzzy logic process
and a second decision-making process based
around levels of quality. Both of these approaches
have been demonstrated individually in other work
(Thomas & Vlacic, 2008; Vlacic & Thomas, 2009).
The decision making process within each
virtual partner results in a recommendation about
how many people to feed, acres to trade and grain
to store. This decision is then passed to the Ac-
tion processor.
In addition to the fuzzy approach, a second
decision-making group was also implemented
which instead made collaborative group decisions
based on levels of quality (LOQ) that each partner
brought to the decision making process. This ap-
proach is based around using a completely neutral
process or mediator to deliver an outcome based
upon the decisions of all partners. Each partner
reviews a set of alternative decisions each turn (in
the case of this computer game, the alternatives
are evaluated and put forward by the partners
themselves) and the group provides their decisions
to the mediator based upon the levels of quality
they have nominated. This electronic mediator
then determines the outcome which satisfies the
decisions of the collaborative group using an
order-consistent achievement function (Vlacic,
Wierzbicki, & Matic, 1986). The electronic me-
diator in the context of this computer game is the
Royal Steward who enacts the outcomes of the
council's decisions.
LOQ Partners 20
16
771
Baseline Part-
ner
16
3
261
Results
The computer game was constructed as a set of
loosely coupled functional modules and sub-
systems. The Hammurabi game module itself is
responsible for creating exogenous game events
and managing game play. To verify the correctness
of the solution, a suite of unit tests was performed
in order to ensure the validity of the computer
game model.
Verification requires benchmarks, testing and
a consistent point of reference. A single reference
implementation 3 of the original Hammurabi was
used to generate testing outcomes with which to
verify the results generated by the game.
Firstly, a Baseline Partner (BP) was used to
determine a benchmark position for game play.
This baseline partner used strict constraints to
ensure the goal of zero population loss per turn.
Two collaborative groups were also tested: A
Fuzzy Logic based collaborative group and a
group collaborating using levels of quality and
an electronic mediator. Finally, a human partner
was also included in testing to verify the solution
approach.
Table 4 shows the results at the end of each
game. The underlined values represent the “win-
ner” of each game attribute (population, bushels
and acres).
What can be seen in Table 4 is that each of
the Human, FP and LOQ strategies in the game
resulted in each achieving a significant benefit over
the others for a particular attribute. Interestingly,
 
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