Bench-MFG: A Benchmark Suite for Learning in Stationary Mean Field Games | ScienceToStartup | ScienceToStartup

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References (38)

[1]

Solving Continuous Mean Field Games: Deep Reinforcement Learning for Non-Stationary Dynamics

2025Lorenzo Magnino, Kai Shao et al.

[2]

Regularization of the policy updates for stabilizing Mean Field Games

2023Talal Algumaei, Rubén Solozabal et al.

[3]

Towards a Standardised Performance Evaluation Protocol for Cooperative MARL

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"Bench-MFG offers a standardized benchmarking suite for evaluating learning algorithms in Mean Field Games, facilitating robust and comparable multi-agent system research."

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Bench-MFG: A Benchmark Suite for Learning in Stationary Mean Field Games

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References (38)

Founder's Pitch

"Bench-MFG offers a standardized benchmarking suite for evaluating learning algorithms in Mean Field Games, facilitating robust and comparable multi-agent system research."

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Bench-MFG: A Benchmark Suite for Learning in Stationary Mean Field Games

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References (38)

Founder's Pitch

"Bench-MFG offers a standardized benchmarking suite for evaluating learning algorithms in Mean Field Games, facilitating robust and comparable multi-agent system research."

Commercial Viability Breakdown

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