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(4) Design thinking is human centered.
As we noted in the introduction, CAD environments have been immensely suc-
cessful in architecture and engineering in large part because they support exper-
imentation, entailing the iterative process of design generation and testing. CAD
environments are also human centered: For example, they provide human designers
with access to visual representations of designs and allow the designers to visually
redesign the designs. Further, they enable humans to make design decisions but they
automate low-level design processes such as constraint propagation.
Of course, design thinking pertains not only to production of physical artifacts, but
also to the creation of abstract artifacts such as art and music, stories and poetry, and
games and movies; hence, our goal of developing GAIA, a CAD-like environment
for designing game-playing software agents. As we described in Sects.
17.3
and
17.4
, GAIA is human-centered: it provides the designer with a visual representation
of the design of the game-playing agent, and supports high-level decision making
while automating low-level processes such as translation of the agent model into
executable code. GAIA enables the designer to reflect on the agent design and its
behavior upon execution in the game world. The REM module within GAIA uses
automated reflection for agent self-adaptation.
17.5.5 Computational Creativity
Finally, we directly relate our work to AI research on computational creativity, the
topic of this volume. AI research on computational creativity goes back at least as
far as the DENDRAL program that identified the structure of chemical molecules
responsible for spectroscopic data [
45
], the BACON program that induced physical
and chemical laws from numerical data [
44
], and the AARON program that drew
abstract paintings [
49
]. The literature typically characterizes creativity in terms of
its product or result: creativity results in products that are (i) novel, (ii) useful or
valuable, and (iii) non-obvious, unexpected or surprising. Colton, Lopez de Man-
taras and Stock [
13
] provide a review of more recent developments in AI research on
computational creativity. These recent developments build in part on psychological
studies [
19
], Sternberg [
72
] socio-psychological studies [
2
], socio-cultural studies
[
67
], and philosophical analysis [
8
] of creativity. For example, Wiggins [
78
] opera-
tionalizes some of Boden's notions about creativity. Colton and Wiggins [
14
]have
called computational creativity the “final frontier” for AI research.
Our work relates to research on computational creativity in two ways. Firstly, we
posit experimentation as a core task in the creative process. Thus, GAIA enables
a designer to address the creative task of designing a game-playing software agent
through experimentation, generating, executing, and revising agent designs until the
designer has constructed an acceptable agent design. Likewise, GAIA can use REM
to automate this process of experimentation in designing game-playing agents.
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