Android Science, Toward a new cross-interdisciplinary framework

In the development of humanoids, both the appearance and behavior of the robots are significant issues.
However, designing the robot’s appearance, especially to give it a humanoid one, was always a role of the
industrial designer. To tackle the problem of appearance and behavior, two approaches are necessary: one
from robotics and the other from cognitive science. The approach from robotics tries to build very
humanlike robots based on knowledge from cognitive science. The approach from cognitive science uses the
robot for verifying hypotheses for understanding humans. We call this cross- interdisciplinary framework
android science. This conceptual paper introduces the developed androids and states the key issues in
android science.

Intelligence as subjective phenomena

How can we define intelligence ? This fundamental question motivates researchers in artificial intelligence
and robotics. Previous works in artificial intelligence considered functions of memory and prediction to
realize the intelligence of artificial systems. After the big wave of artificial intelligence in the 1980’s
and 1990’s, researchers focused on the importance of embodiment and started to use robots. The behavior-
based system proposed by Brooks was a trigger for this new wave. This means the main focus on artificial
intelligence and robotics has changed from an internal mechanism to interaction with the environment.
On the other hand, there are also two ideas in cognitive science. One is to focus on the internal
mechanism for understanding human intelligent behaviors, while the other focuses on the interactions
among people. This  approaches is studied in the framework of distributed cognition. The idea of
distributed cognition has similar aspects to the behavior-based system. The common concept is to
understand intelligence through human-human or human-robot interactions. This is also follows the ideas
of the behavior-based systems and distributed cognition. Because intelligence is a subjective phenomena,
it is therefore important to implement rich interactive behaviors with the robot. The author believes the
development of rich interactions among robots will provide hints of principles of communication systems,
with the design methodology of intelligent robots then being derived from those principles.

Constructive approach in robotics

First we have the question of how to develop the robots. There are explicit evaluation criteria for robot
navigation such as speed, precision, etc. On the other hand, our purpose is also to develop interactive
robots. If we have enough knowledge of humans, we may have explicit evaluation criteria. However this
knowledge is not sufficient to provide a top-down design; instead the potential approach is rather
bottom-up. By utilizing available sensors and actuators, we can design the behaviors of a robot and then
decide the execution rules among those behaviors. While doing this developing, we also evaluate the
robot’s performance and modify the behaviors and execution rules. This bottom-up approach is called the
constructive approach .In the constructive approach, interactions between a robot and a human are often
evaluated and analyzed through discussions with cognitive scientists and psychologists, with the robot
then being improved by the knowledge obtained through the discussions.

Appearance and behavior

In the evaluation, the performance measures are subjective impression of human subjects who interact with
the robot and their unconscious reactions, such as synchronized human behaviors in the interactions and eye
movements. Obviously, both the appearance and behavior of the robots are important factors in this
evaluation. There are many technical reports that compare robots with different behaviors. However nobody
has focused on appearance in the previous robotics. There many empirical discussions on very simplified
static robots, say dolls. Designing the robot’s appearance, especially to give it a humanoid one, was always
a role of the industrial designer. However we consider this to be a serious problem for developing and
evaluating interactive robots. Appearance and behavior are tightly coupled with both each other and these
problems, as the results of evaluation change with appearance. We developed several
humanoids for communicating with people, as shown in Figure 1. We empirically know the effect of appearance
is as significant as behaviors in communication. Human brain functions that recognize people support our
empirical knowledge.

Figure 1: From humanoids to androids. The first robot (the left end) is Robovie II developed by ATR
Intelligent Robotics and Communications Laboratories. The second is Wakamaru developed by Mitsubishi
Heavy Industry Co. Ltd. The third is a child android, while the fourth is the master of the child android.

Android Science

To tackle the problem of appearance and behavior, two approaches are necessary: one from robotics and the
other from cognitive science. The approach from robotics tries to build very humanlike robots based on
knowledge from cognitive science. The approach from cognitive science uses the robot for verifying hypotheses
for understanding humans. We call this cross-interdisciplinary framework android science.

Figure 2: The framework of android science

Previous robotics research also used knowledge of cognitive science while research in cognitive science
utilized robots. However the contribution from robotics to cognitive science was not enough as robot-like
robots were not sufficient as tools of cognitive science, because appearance and behavior cannot be separately
handled. We expect this problem to be solved by using an android that has an identical appearance to a human.
Robotics research utilizing hints from cognitive science also has a similar problem as it is difficult to
clearly recognize whether the hints are given for just robot behaviors isolated from their appearance or for
robots that have both the appearance and the behavior. In the framework of android science, androids enable us
to directly exchange knowledge between the development of androids in engineering and the understanding of
humans in cognitive science.

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