Mathematical and Algorithmic Foundations of Artificial Intelligence in Complex System Modeling and Autonomous Multi-Agent Interactions
Keywords:
Artificial Intelligence, Complex System Modeling, Multi-Agent Systems, Game Theory, Optimization, Reinforcement Learning, Graph TheoryAbstract
Artificial Intelligence (AI) has revolutionized the field of complex system modeling and multi-agent interactions, offering advanced computational techniques for predictive analysis, decision-making, and autonomous system control. This paper explores the mathematical and algorithmic foundations underpinning AI models in complex system modeling and autonomous multi-agent interactions. We discuss key mathematical techniques, including graph theory, game theory, optimization methods, and probabilistic reasoning. Furthermore, we review pre-2023 literature to highlight significant advancements and challenges. The paper includes a detailed discussion of AI-driven multi agent interactions, optimization techniques for dynamic systems, and simulation frameworks. By providing an analytical and empirical overview, we aim to contribute to the ongoing development of robust AI-driven methodologies for complex system management.
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