June 23rd, 2006


A.I./Swarm Int.

Communicating Agents: allow machines to evolve their own language

Most research into the Artificial Intelligence (AI) that underpins any form of intelligent machine-machine or machine-human interaction has centred on programming the machine with a set of predefined rules. Researchers have, in effect, attempted to build robots or devices with the communication skills of a human adult. That is a shortcut that ignores the evolution of language and the skills gained from social interaction, thereby limiting the ability of AI devices to react to stimuli to within a fixed set of parameters.

...Whereas we 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. This, the researchers achieved through instilling their robots with a sense of ‘curiosity.’ - Press release

ECAgents project



Nature Reviews Neuroscience, July 2006
Variability, compensation and homeostasis in neuron and network function

...each neuron is constantly rebuilding itself from its constituent proteins, using all of the molecular and biochemical machinery of the cell. This allows for plastic changes in development and learning, but also poses the problem of how stable neuronal function is maintained as individual neurons are continuously replacing the proteins that give them their characteristic electrophysiological signatures...

from Conclusions:

Variability and compensation are not specific networks of neurons. Such properties have also been described for biochemical and genetic regulation networks. These networks ...are able to adapt to modifications of their components to maintain the same output, even if one of their components is deleted. This has sometimes been attributed to redundancy, but is much more likely to be a consequence of the potential for compensation among components with different properties. In fact, unlike in engineering, in which redundant systems often consist of two or three copies of identical devices, such as electrical generators or navigation systems, in biological systems there are probably no truly redundant processes, but system robustness and flexibility are achieved simultaneously through overlapping functions and compensation.