Author(s)

A. D'Angelo

Abstract

Classical planners, which automatically generate plans to be executed as a sequence of primitive actions cannot follow their actual execution because they cannot compare and modify its behaviour continuously using sensor data flow. On the other hand, autonomous systems need to interact with the environment because they have an incomplete knowledge about it. So, the planner doesn't pretend to generate explicitly all the actions. In this paper we propose an alter- native way to design and build an autonomous system introducing the metaphor of biochemical machine. We think of the whole system as a family of behaviours, each implementing a set of actions which specify, at each step, the most appro- priate response to a pe

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