Field:
Theoretical and Applied Mathematics/Informatics
Session Topic:
Computational Neuroscience for Humanoids
Speaker:
Itsuki Noda/National Institute of Advanced Industrial Science and Technology
1. Introduction
By the year 2050, develop a team of fully autonomous humanoid robots
that can win against the human world soccer (football) champion team.
This is a statement about the ultimate goal of RoboCup project, which is an
international joint project to promote artificial intelligence (AI), robotics, and related
field by providing a standard problem where wide range of technologies can be
integrated and examined. While the goal is simple and attractive, we do not intend to
develop a kind of super robot who has more powerful body and complete sensing
devices than human-being. Instead, we are aiming to develop really human-like
robots (humanoids) who can play soccer with us. Here, “play with us” means the we,
human-being, and humanoids can communicate and understand with each other.
2. Directions of Research on Humanoid
There are two directions of research to realize such humanoids. The first direction is
to realize robots that behave like human, and the second is to investigate human’s
intelligent response.
The most of researches on humanoids follow the first direction[Hirukawa et.al 2005,
Yamasaki et.al. 2002]. In this direction, we had remarkable progress in these ten
years. This progress, however, is mainly done in movement facilities like standing
and walking by two legs. On the other hand, methodologies for intelligent behaviors
are not improved so much.
The main reason of this less progress on intelligence is that it is difficult to define
what is intelligence. Recently, many AI researchers become to think that intelligence
can not exist stand-alone.
Instead, we believe that intelligence can be
understandable only with body through interaction with human-being. This is the
reason why the second direction is focused [Oztop et.al 2005, Ishiguro and Minato
2005].
3. How to Imitate of Human Intelligent Behaviors
Imitation is a key issue when we investigate human intelligence with body and
interaction. Initially, imitation was focused to develop a framework to control
complex systems of humanoids [Schaal 1999]. This is effective when we try to make
humanoid behave emotional or artistic actions. Imitation is also considered as an
important factor of high level processes in brain after the discovery of mirror neuron
[Rizzolatti et.al. 2000]. Inspired by the mirror neuron, several works have been done
to apply imitation for humanoid to re-produce human-like behavior.
I have been also applying the similar idea to imitate team-plays, which consists of
collections of sequence of actions among multiple agents (virtual robots) [Noda 2003].
A hierarchically coupled hidden Markov model (HMM) is utilized to learn combination
plays between two soccer agents (Fig.1). Because a team play is a synchronized
action sequences among multiple agents, timing control to transit from an action to
another in each agent is the main issue to imitate the team play. The coupled HMM
enables to model and learn this timing control by observation effectively. I also
showed that the modular structure of this model, whose components correspond
intentions of actions, can reduce computational complexity. As a result, the model
can apply one-shot learning that requires only one example or demonstrations of the
imitating team-plays.
The proposed model is still simple and naïve, so that it is still open problem to
realize imitation of more complex combinations of actions and interactions. It is also
an open issue to find corresponding phenomena or structure in actual brain. In order
to attack these issues, collaboration of works on AI/robotics and brain science as a
research of understanding human intelligence is required.
Fig. 1 Team Play Imitation using Hidden Markov Model
Conclusion
I discussed two directions of humanoid researches and considered an importance of
imitation in these researches. While the current works on the imitation are rather
low-level and naïve to approach mystery of intelligence, there will be many possibility
to understand various phenomena in neuron-level and cooperative-behavior-level
based-on the concept of imitation. In addition, social phenomena like economy may
be able to be investigated using imitation as a core operator [Izumi and Ueda 2002].
References
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International Journal of Psychology 35: 205-205, 2000.
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