Mathematical Framework for ABM-MARL Integration in Financial Systems: A Discrete Multi-Agent Population-Strategy Game Approach

Agaricus blazei

Cognition & nerves

SpeciesAlmond Mushroom, ABM

JournalNot listed

Year2025

Key points

Abstract Modern financial markets feature complex interactions between vast populations of rule-based agents and adaptive algorithmic traders, yet existing models treat these layers separately
We introduce a discrete-time population-strategy game unifying Agent-Based Modeling (ABM) and Multi-Agent Reinforcement Learning (MARL) with five core innovations: (1) an asymmetric bilevel architecture where strategic agents optimize over population distributions while endogenously shaping them; (2) heavy-tailed α-stable noise (1

From the paper

Abstract

Abstract Modern financial markets feature complex interactions between vast populations of rule-based agents and adaptive algorithmic traders, yet existing models treat these layers separately. We introduce a discrete-time population-strategy game unifying Agent-Based Modeling (ABM) and Multi-Agent Reinforcement Learning (MARL) with five core innovations: (1) an asymmetric bilevel architecture where strategic agents optimize over population distributions while endogenously shaping them; (2) heavy-tailed α-stable noise (1

Citation

Samal B (2025). Mathematical Framework for ABM-MARL Integration in Financial Systems: A Discrete Multi-Agent Population-Strategy Game Approach. https://doi.org/10.21203/rs.3.rs-7326746/v1

Open citation