Paper: arXiv 2212.07942
Authors: Alexis Asseman, Tomasz Kornuta, Anirudh Patel, Matt Deible, Sam Green
Abstract
The Graph Protocol indexes historical blockchain transaction data and makes it available for querying. As the protocol is decentralized, there are many independent Indexers that index and compete with each other for serving queries to the Consumers. One dimension along which Indexers compete is pricing. In this paper, we propose a bandit-based algorithm for maximization of Indexers’ revenue via Consumer budget discovery. We present the design and the considerations we had to make for a dynamic pricing algorithm being used by multiple agents simultaneously. We discuss the results achieved by our dynamic pricing bandits both in simulation and deployed into production on one of the Indexers operating on Ethereum. We have open-sourced both the simulation framework and tools we created, which other Indexers have since started to adapt into their own workflows.
Complexity vs Empirical Score
- Math Complexity: 5.5/10
- Empirical Rigor: 7.5/10
- Quadrant: Holy Grail — high math complexity, high empirical rigor
Why this score: This paper offers a strong bridge between multi-agent bandit theory and real-world deployment on decentralised blockchain infrastructure. It demonstrates high practical value and empirical rigor through both simulation and production evaluation, alongside open-sourced tooling.
Research Flowchart
flowchart TD
A[Research Goal: Maximize Indexer Revenue via Dynamic Pricing in The Graph Protocol] --> B[Design Gaussian Multi-Armed Bandit Algorithm for Budget Discovery]
B --> C[Data Inputs: Historical Blockchain Data, Consumer Budgets, & Competitor Pricing]
C --> D[Simulate Multi-Agent Pricing Dynamics]
D --> E[Deploy Bandit Algorithm to Production Ethereum Indexer]
E --> F[Outcomes: Validated Revenue Maximization & Open-Source Tools Adopted by Indexers]