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20202025
most citedTowards a Theory of Maximal Extractable Value I: Constant Function Market Makers

16 citations · 22 across the 12 of their papers we have counts for

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7 papers · 1 filter

cs.GT2025

Optimal Routing in the Presence of Hooks: Three Case Studies

Tarun Chitra, Kshitij Kulkarni, Karthik Srinivasan

We consider the problem of optimally executing a user trade over networks of constant function market makers (CFMMs) in the presence of hooks. Hooks, introduced in an upcoming vers…

cs.GT2024

Adaptive Incentive Design with Learning Agents

Chinmay Maheshwari, Kshitij Kulkarni, Manxi Wu +1

We propose an adaptive incentive mechanism that learns the optimal incentives in environments where players continuously update their strategies. Our mechanism updates incentives b…

cs.GT2024★ 1 cited

An Analysis of Intent-Based Markets

Tarun Chitra, Kshitij Kulkarni, Mallesh Pai +1

Mechanisms for decentralized finance on blockchains suffer from various problems, including suboptimal price execution for users, latency, and a worse user experience compared to t…

cs.GT2024

Congestion Pricing for Efficiency and Equity: Theory and Applications to the San Francisco Bay Area

Chinmay Maheshwari, Kshitij Kulkarni, Druv Pai +3

Congestion pricing, while adopted by many cities to alleviate traffic congestion, raises concerns about widening socioeconomic disparities due to its disproportionate impact on low…

cs.GT2023

Credible, Optimal Auctions via Public Broadcast

Tarun Chitra, Matheus V. X. Ferreira, Kshitij Kulkarni

We study auction design in a setting where agents can communicate over a censorship-resistant broadcast channel like the ones we can implement over a public blockchain. We seek to…

cs.GT2022★ 16 cited

Towards a Theory of Maximal Extractable Value I: Constant Function Market Makers

Kshitij Kulkarni, Theo Diamandis, Tarun Chitra

Maximal Extractable Value (MEV) refers to excess value captured by miners (or validators) from users in a cryptocurrency network. This excess value often comes from reordering user…

cs.GT2022★ 1 cited

Inducing Social Optimality in Games via Adaptive Incentive Design

Chinmay Maheshwari, Kshitij Kulkarni, Manxi Wu +1

How can a social planner adaptively incentivize selfish agents who are learning in a strategic environment to induce a socially optimal outcome in the long run? We propose a two-ti…