Evaluation of Multi-Armed Bandit Decision Making in Multi-Agent Cyber Physical Games

Efficient decision-making in Cyber Physical Systems is hindered by their inherent non-deterministic nature. Statistical methods are required to obtain well performant solutions, especially in the context of multi-agent systems that interfere with one another. We experimentally evaluate Multi-Armed Bandits, a class of statistical methods that balances the trade-off between exploration and exploitation, on Cyber Physical Games, a specific instance of emergent properties of multi-agent Cyber Physical Systems. We show Multi-Armed Bandits can efficiently identify adequate strategies for decision-making, outperforming baseline approaches.