Teaching robot dogs linguistic tricks

22 June 2006

Researchers led by the Institute of Cognitive Science and Technology in Italy are developing robots that evolve their own language, bypassing the limits of imposing human rule-based communication.

“The result is machines that evolve and develop by themselves without human intervention,” said Stefano Nolfi, the coordinator the ECAgents project. The project, financed by the European Commission’s Future and Emerging Technologies (FET) initiative, has brought together researchers from disciplines as diverse as robotics, linguistics and biology.

The technology, dubbed Embedded and Communicating Agents, has allowed researchers at Sony’s Computer Science Laboratory in France to add a new level of intelligence to the AIBO dog. Instead of teaching the dog new tricks, the algorithms, design principles and mechanisms developed by the project allow the robotic pet to learn new tricks itself and share its knowledge with others.

“What has been achieved at Sony shows that the technology gives the robot the ability to develop its own language with which to describe its environment and interact with other AIBOs. It sees a ball and it can tell another one where the ball is, if it’s moving and what colour it is, and the other is capable of recognising it,” Nolfi said.

The most important aspect is how it learns to communicate and interact. Whereas humans use the word ‘ball’ to refer to a ball, the AIBO dogs start from scratch to develop common agreement on a word to use to refer the ball. They also develop the language structures to express, for instance, that the ball is rolling to the left. The researchers achieved this through instilling their robots with a sense of ‘curiosity.’

Initially programmed to recognise stimuli from their sensors, the AIBOs learnt to distinguish between objects and how to interact with them over the course of several hours or days. The curiosity system, or ‘metabrain,’ continually forced the AIBOs to look for new and more challenging tasks, and to give up on activities that did not appear to lead anywhere. This in turn led them to learn how to perform more complex tasks, an indication of an open-ended learning capability much like that of children.

Also like children, the AIBOs initially started babbling aimlessly until two or more settled on a sound to describe an object or aspect of their environment, gradually building a lexicon and grammatical rules through which to communicate.

“This is not only important from a robotics and AI perspective, it could also help us understand how language systems arise in humans and animals,” Nolfi said.

The success of the evolutionary and social learning approach taken to developing AI by the project has also been demonstrated in other trials.

In tests run at the Swiss Federal Institute of Technology in Lausanne, hordes of small wheeled robots learnt how to communicate, cooperate and self-organise to perform tasks that would be too complicated for a single robot.

“The technology could lead to robots able to carry out rescue operations by swarming over inaccessible areas to find people,” Nolfi said.

“This is a project with a big impact. We’ve managed to ground AI in reality, in the real world, solving one of the crucial problems to creating truly intelligent and cooperative systems.”