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We propose a generic reward shaping approach for improving the rate of convergence in reinforcement learning (RL), called Self Improvement Based REwards, or SIBRE. The approach is designed for use in conjunction with any existing RL…

Machine Learning · Computer Science 2020-12-22 Somjit Nath , Richa Verma , Abhik Ray , Harshad Khadilkar

This work investigates the potential of undermining both fairness and detection performance in abusive language detection. In a dynamic and complex digital world, it is crucial to investigate the vulnerabilities of these detection models to…

Computation and Language · Computer Science 2023-12-07 Yueqing Liang , Lu Cheng , Ali Payani , Kai Shu

We derive an accounting identity for predictive models that links accuracy with common fairness criteria. The identity shows that for globally calibrated models, the weighted sums of miscalibration within groups and error imbalance across…

Machine Learning · Computer Science 2026-01-29 Hadi Elzayn , Jacob Goldin

This paper presents a novel staking coopetition design aimed at incentivizing decentralization and continuous growth of economic security within a proof-of-stake system. Staking rewards follow a nonlinear mapping relative to stake size.…

Theoretical Economics · Economics 2025-05-19 Michael D. Norman , Simon Brown , Mallesh Pai , Laurence Smith

Metagenomics has revealed hundreds of bacterial species in almost all microbiota. In a few well-studied cases, bacterial communities have been observed to coordinate their metabolic fluxes. In principle, bacteria can divide tasks to reap…

Populations and Evolution · Quantitative Biology 2016-04-12 Thibaud Taillefumier , Anna Posfai , Yigal Meir , Ned S. Wingreen

In retrospect, the experimental findings on competitive market behavior called for a revival of the old, classical, view of competition as a collective higgling and bargaining process (as opposed to price-taking behaviors) founded on…

General Finance · Quantitative Finance 2023-07-04 Sabiou Inoua , Vernon Smith

This paper studies the problem of maximizing the expected utility of terminal wealth for a financial agent with an unbounded random endowment, and with a utility function which supports both positive and negative wealth. We prove the…

Portfolio Management · Quantitative Finance 2008-12-10 Mark Owen , Gordan Zitkovic

In the problem of allocating a single non-disposable commodity among agents whose preferences are single-peaked, we study a weakening of strategy-proofness called not obvious manipulability (NOM). If agents are cognitively limited, then NOM…

Theoretical Economics · Economics 2024-04-25 R. Pablo Arribillaga , Agustin G. Bonifacio

We study strong equilibria in symmetric capacitated cost-sharing games. In these games, a graph with designated source $s$ and sink $t$ is given, and each edge is associated with some cost. Each agent chooses strategically an $s$-$t$ path,…

Computer Science and Game Theory · Computer Science 2016-11-18 Michal Feldman , Ofir Geri

With the fragmentation of electronic markets, exchanges are now competing in order to attract trading activity on their platform. Consequently, they developed several regulatory tools to control liquidity provision / consumption on their…

Optimization and Control · Mathematics 2022-10-17 Bastien Baldacci , Philippe Bergault

Conventional models of matching markets assume that monetary transfers can clear markets by compensating for utility differentials. However, empirical patterns show that such transfers often fail to close structural preference gaps. This…

Trading and Market Microstructure · Quantitative Finance 2025-11-27 Yao Wu

Convergence of Extremum Seeking (ES) algorithms has been established in the limit of small gains. Using averaging theory and contraction analysis, we propose a framework for computing explicit bounds on the departure of the ES scheme from…

Optimization and Control · Mathematics 2013-03-20 Gabriel Bousquet , Jean-Jacques Slotine

Deploying guardrails for custom policies remains challenging, as generic safety models fail to capture task-specific requirements, while prompting LLMs suffers from inconsistent boundary-case performance and high inference costs. Training…

Computation and Language · Computer Science 2026-04-29 Arnon Mazza , Elad Levi

Global supply networks in agriculture, manufacturing, and services are a defining feature of the modern world. The efficiency and the distribution of surpluses across different parts of these networks depend on choices of intermediaries.…

General Finance · Quantitative Finance 2019-06-05 Felipe M. Cardoso , Carlos Gracia-Lazaro , Frederic Moisan , Sanjeev Goyal , Angel Sanchez , Yamir Moreno

If two species exhibit different nonlinear responses to a single shared resource, and if each species modifies the resource dynamics such that this favors its competitor, they may stably coexist. This coexistence mechanism, known as…

Populations and Evolution · Quantitative Biology 2015-06-16 Florian Hartig , Tamara Münkemüller , Karin Johst , Ulf Dieckmann

We study an online allocation problem with sequentially arriving items and adversarially chosen agent values, with the goal of balancing fairness and efficiency. Our goal is to study the performance of algorithms that achieve strong…

Computer Science and Game Theory · Computer Science 2023-08-21 Zongjun Yang , Luofeng Liao , Christian Kroer

Strategic behavior against sequential learning methods, such as "click framing" in real recommendation systems, have been widely observed. Motivated by such behavior we study the problem of combinatorial multi-armed bandits (CMAB) under…

Machine Learning · Computer Science 2021-11-22 Jing Dong , Ke Li , Shuai Li , Baoxiang Wang

We study superreplication of European contingent claims in discrete time in a large trader model with market indifference prices recently proposed by Bank and Kramkov. We introduce a suitable notion of efficient friction in this framework,…

Pricing of Securities · Quantitative Finance 2013-10-14 Peter Bank , Selim Gökay

Optimizing objective functions subject to constraints is fundamental in many real-world applications. However, these constraints are often not readily defined and must be inferred from expert agent behaviors, a problem known as Inverse…

Machine Learning · Computer Science 2025-05-19 Bo Yue , Jian Li , Guiliang Liu

Preventing fake or duplicate digital identities (aka sybils) from joining a digital community may be crucial to its survival, especially if it utilizes a consensus protocol among its members or employs democratic governance, where sybils…

Social and Information Networks · Computer Science 2023-12-11 Ouri Poupko , Gal Shahaf , Ehud Shapiro , Nimrod Talmon