Multi-Coalition Multi-Agent Decision Making System Synthesis
Keywords:
nature-inspired computing, membrane computing, cell computing, P-systems, swarm computing, collective decision making, multi-agent systems, multi-criteria optimization, genetic algorithm, goal, strategy, reconfigurable architectureAbstract
This research explores the interdisciplinary field of nature-inspired computing, which relies on biological models and processes to develop innovative algorithms and computational systems. The paper analyzes the main categories in this field: evolutionary computing, collective intelligence, biological systems, as well as advanced approaches, such as cellular and membrane models. These paradigms provide robust and scalable solutions to complex problems that are difficult to address by traditional methods. The research places particular emphasis on cell computing, which reproduces the structure and functionality of biological cells, and on membrane computing, which introduces concepts of hierarchy and distributed processing. At the same time, the paper proposes an innovative methodology for the design of Multi-Agent systems, based on these biological models, including the dynamic formation of coalitions and the optimization of interactions between autonomous agents. The main contribution lies in the development of a mathematical model and a functional architecture for the integration of these paradigms, promoting collaborative, resilient, and innovative solutions for the future of distributed artificial intelligence.
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