Compromising Algorithmicity and Plasticity in Autonomous Agent Control Architectures: The Autonomous Cell

Elpida S. Tzafestas
<span title="">1999</span> <i title="Walter de Gruyter GmbH"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/fvcuwwb4brauziwelchs6y6lzi" style="color: black;">Journal of Intelligent Systems</a> </i> &nbsp;
While algorithmic autonomous agent control architectures demonstrate high efficiency, they suffer from network structure rigidity that shows in the liability to crucial errors. On the other hand, the redundancy inherent in most connectionist architectures allows for continuous self-organization that compensates for limited-scale neuron failures. In this work, we are seeking to compromise algorithmicity and plasticity in front of local network failures, by extending a basic algorithmic cell
more &raquo; ... . The extension is twofold : on the one hand we introduce motivation to the cell level, which shows as preference to consume some kinds of messages, while on the other hand we introduce sociality, which shows as adaptivity of the cell to the motivations of its neighbors. Unlike usual connectionist models, there are no connections between cells, but message buffers shared by all cells of a level ; this way, cells can be viewed as floating in a common interaction medium and competing with one another. Another important feature of this arrangement is the necessity of an immune system, i.e., a population of cells that recognize and eliminate the messages that might be detrimental to the integrity of the cellular agent. The model's self-organizational potential is illustrated on the example case of a navigation system. Our simulation results show that the cellular network exhibit plasticity and recover from various types of failures by "discovering" alternative message flow pathways and that multiple failures slow down the system's responsiveness to external events. Issues such as selectivity and the role of diversity are also discussed.
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