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Found 8 papers, 0 papers with code
Interventionally Consistent Surrogates for Agent-based Simulators
Agent-based simulators provide granular representations of complex intelligent systems by directly modelling the interactions of the system's constituent agents.
JAX-LOB: A GPU-Accelerated limit order book simulator to unlock large scale reinforcement learning for trading
Financial exchanges across the world use limit order books (LOBs) to process orders and match trades.
Generative AI for End-to-End Limit Order Book Modelling: A Token-Level Autoregressive Generative Model of Message Flow Using a Deep State Space Network
Overall, our results invite the use and extension of the model in the direction of autoregressive large financial models for the generation of high-frequency financial data and we commit to open-sourcing our code to facilitate future research.
Some challenges of calibrating differentiable agent-based models
Agent-based models (ABMs) are a promising approach to modelling and reasoning about complex systems, yet their application in practice is impeded by their complexity, discrete nature, and the difficulty of performing parameter inference and optimisation tasks.
Bayesian calibration of differentiable agent-based models
Agent-based modelling (ABMing) is a powerful and intuitive approach to modelling complex systems; however, the intractability of ABMs' likelihood functions and the non-differentiability of the mathematical operations comprising these models present a challenge to their use in the real world.
Supply Chain Digital Twin Framework Design: An Approach of Supply Chain Operations Reference Model and System of Systems
This paper explains what is 'twined' in supply chain digital twin and how to 'twin' them to handle the spatio-temporal dynamic issue.
Digital Twins: State of the Art Theory and Practice, Challenges, and Open Research Questions
This work explores the various DT features and current approaches, the shortcomings and reasons behind the delay in the implementation and adoption of digital twin.
How Market Ecology Explains Market Malfunction
Here we develop an alternative based on concepts and methods developed by biologists, in which the wealth invested in a financial strategy is like the abundance of a species.
