毕竟Agent-based modeling的支持者批评的是主流理论里agent做Bayesian updating的惯例。所以取另一个极端—...
因而是一种adaptation，但通常不被称为狭义的learning，因为，这种算法是否是对agent而言最优的，没有保障...
Machine learningSensitivity analysisPleistoceneGlobalClimate dynamicsPaleogeographyData treatmentUnderstanding Late Pleistocene human dispersals from Africa requires understanding a multifaceted problem with factors varying in space and time, such as climate, ecology, human behavior, and population dynamics. To ...
L-FABS combines agent-based simulation with machine learning to model the behavior of financial time series.We also discuss why Partial Knowledge and Full Knowledge learning scenario are relevant to the modeling of financial time series and how they can be used to assess the robustness of a ...
Agent-Based Models (ABMs) are used in several fields to study the evolution of complex systems from micro-level assumptions. However, a significant drawback of ABMs is their inability to estimate agent-specific (or “micro”) variables, which hinders the
To remove these constrictive assumptions and improve agent modeling performance, we devised a Contrastive Learning-based Agent Modeling (CLAM) method that relies only on the local observations from the ego agent during training and execution. With these observations, CLAM is capable of generating ...
LLM empowered agent-based modeling and simulation A summary of works on LLM empowered agent-based modeling and simulation. Our survey Large language models empowered agent-based modeling and simulation: a survey and perspectives is accepted by Humanities and Social Sciences Communications. A preprint is...
Agent-based modeling and simulation have evolved as a powerful tool for modeling complex systems, offering insights into emergent behaviors and interactions among diverse agents. Recently, integrating large language models into agent-based modeling and s
Agent-based modeling and simulation (ABMS) is an approach to modeling systems comprised of individual, autonomous, interacting "agents." There is much inte... CM Macal,MJ North - IEEE 被引量: 129发表: 2011年 Machine learning in agent-based stochastic simulation: Inferential theory and evaluatio...
Target audience.The workshop will provide a forum for social scientists, policy-makers, and AI, MAS and simulation researchers and developers, to assess the current state of the art in the agent-based modeling and simulation of...