A memory-learning collaborative agent model with hierarchical individual/collective memory and dynamic filtering improves simulated delivery agents' profit and stability compared with existing memory models.
Computational Experiments: Past, Present and Future
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abstract
Powered by advanced information technology, more and more complex systems are exhibiting characteristics of the Cyber-Physical-Social Systems (CPSS). Understanding the mechanism of CPSS is essential to our ability to control their actions, reap their benefits and minimize their harms. In consideration of the cost, legal and institutional constraints on the study of CPSS in real world, computational experiments have emerged as a new method for quantitative analysis of CPSS. This paper outlines computational experiments from several key aspects, including origin, characteristics, methodological framework, key technologies, and some typical applications. Finally, this paper highlights some challenges of computational experiments to provide a roadmap for its rapid development and widespread application.
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MLC-Agent: Cognitive Model based on Memory-Learning Collaboration in LLM Empowered Agent Simulation Environment
A memory-learning collaborative agent model with hierarchical individual/collective memory and dynamic filtering improves simulated delivery agents' profit and stability compared with existing memory models.