| Abstrakt: |
This article hypothesizes that the presence of well-protected memory of sensor networks improves their performance as a multi-agent system. The agent’s memory stores information about typical reactions to information signals from receptors, as well as information about the state of effectors and available resources. It also stores programs for processing input information into control signals supplied to effectors and the results of reactions to a particular external situation, the number and variety of knowledge and programs stored in it, the degree of development of the internal model of the external world, and reflection options that determine the complexity and nature of behavior agent. The main components of the memory block are filter systems that provide the most important information for the agent, the internal model of the outside world, and the model of the agent itself. Purpose: to prove that using the FPGA platform guarantees programmable memory protection to maintain its level of autonomy and intelligence. The object of study: cybersecurity of sensor networks with protected memory Approaches: agent theory, machine learning Objective: To prove that the use of the FPGA platform guarantees programmable memory protection to maintain its level of autonomy and intelligence. Findings: sensor network security models [ABSTRACT FROM AUTHOR] |
