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Parameter Optimization and Emergent Behavior in DeFi: Agent Based Simulations and Reinforcement Learning

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Parameter Optimization and Emergent Behavior in DeFi: Agent Based Simulations and Reinforcement Learning

Duration: 00:00:00

Speaker: David Siska, Marc, Tom McLean

Type: Workshop

Expertise:

Event: Devcon 6

Date: Oct 2022

As in any complex system there may be emergent behaviors in DeFi protocols. In this workshop we will show the basics of how agent based simulations combined with reinforcement learning can be used to explore these and also for optimization of various protocol parameter values. This will be based on https://github.com/vegaprotocol/vega-market-sim and https://github.com/msabvid/cpm_agent_based_sim . Participants should have Python / Pytorch if they want to hack along.
About the speakers

DS

David Siska

I am currently a Head of Research at Vega protocol and Associate Professor of Mathematics at the University of Edinburgh. I've been interested in programming from an early age, oscillating between applied problems (coding) and theoretical (mathematics). At Vega I am mainly focused on whole system modelling, design validation and development of new protocol features. My maths research is on the theoretical aspects of reinforcement learning and optimal control algorithms.

M

Marc

TM

Tom McLean

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