Learning and Calibrating Heterogeneous Bounded Rational Market Behaviour with Multi-Agent Reinforcement Learning
By Benjamin Patrick Evans, Sumitra Ganesh
Rating
1423
Battle Count: 26
Relevance
8/10
The approach provides a more realistic model of market participant behavior, which could improve market simulations and strategy testing for quantitative trading
Implementation Complexity
7/10
Requires implementation of custom MARL algorithms and understanding of behavioral economics concepts
Reproducibility
4/5
The paper provides detailed methodology and experimental setup, but some implementation details may require further clarification
About this paper
Methodology: Heterogeneous Bounded Rational MARL. Problem types: Multi-agent Learning, Market Simulation, Behavioral Modeling.
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