Growing Up of Autonomous Agents: an Emergent Phenomenon

A fundamental research challenge is the design of robust artifacts that are capable of operating under Changing environments and noisy input, and yet exhibit the desired behavior and response time. These systems should be able to adapt and learn how to react to unforeseen scenarios as well as to display properties comparable to biological entities. The turn to nature has brought LIS many unforeseen great concepts. Biological systems are able to handle many of these challenges with an elegance and efficiency still far beyond current human artifacts. A living artifact grows up when its capabilities, abilities/knowledge, shift to a fin-flier level of complexity, i.e. the complexity rank of its internal capabilities performs a step forward. In the attempt to define an architecture for autonomous growing up agents [1]. We conducted an experiment on the abstraction process in children as natural parts of a cognitive system. We found that linguistic growing up involve a number of different trial processes, We identified a fixed number of distinct paths that were crossed by children. Once a given interpretation paths was discovered useless, they tried to follow another path, until the new meaning was emerging. This study generates suggestion about the evolutionary conditions conducive to the emergence of growing up in robots and provides guidelines for designing artificial evolutionary systems displaying spontaneous adaptation abilities. The importance of multi-sensor perception, motivation and emotional drives are underlined and, above all, the growing up insights shows similarities to emergent self-organized behaviors.