5 citations · 17 across the 10 of their papers we have counts for
13 papers
The Delegation Dilemma: Economies of Scale, Accountability, and Polycentric Governance
Arin Mukhopadhyay, Aris Filos-Ratsikas, Panayiotis Danassis
Many collective-action systems are neither fully decentralized nor fully centralized: agents voluntarily organize into institutions that share organizational costs and delegate dec…
Can Vibe Coding Beat Graduate CS Students? An LLM vs. Human Coding Tournament on Market-driven Strategic Planning
Panayiotis Danassis, Naman Goel
The rapid proliferation of Large Language Models (LLMs) has revolutionized AI-assisted code generation. This rapid development of LLMs has outpaced our ability to properly benchmar…
Lazy But Effective: Collaborative Personalized Federated Learning with Heterogeneous Data
Ljubomir Rokvic, Panayiotis Danassis, Boi Faltings
In Federated Learning, heterogeneity in client data distributions often means that a single global model does not have the best performance for individual clients. Consider for exa…
Improving Health Information Access in the World's Largest Maternal Mobile Health Program via Bandit Algorithms
Arshika Lalan, Shresth Verma, Paula Rodriguez Diaz +6
Harnessing the wide-spread availability of cell phones, many nonprofits have launched mobile health (mHealth) programs to deliver information via voice or text to beneficiaries in…
Limited Resource Allocation in a Non-Markovian World: The Case of Maternal and Child Healthcare
Panayiotis Danassis, Shresth Verma, Jackson A. Killian +2
The success of many healthcare programs depends on participants' adherence. We consider the problem of scheduling interventions in low resource settings (e.g., placing timely suppo…
LIA: Privacy-Preserving Data Quality Evaluation in Federated Learning Using a Lazy Influence Approximation
Ljubomir Rokvic, Panayiotis Danassis, Sai Praneeth Karimireddy +1
In Federated Learning, it is crucial to handle low-quality, corrupted, or malicious data. However, traditional data valuation methods are not suitable due to privacy concerns. To a…
Improving Multi-agent Coordination by Learning to Estimate Contention
Panayiotis Danassis, Florian Wiedemair, Boi Faltings
We present a multi-agent learning algorithm, ALMA-Learning, for efficient and fair allocations in large-scale systems. We circumvent the traditional pitfalls of multi-agent learnin…
AI-driven Prices for Externalities and Sustainability in Production Markets
Panayiotis Danassis, Aris Filos-Ratsikas, Haipeng Chen +2
Traditional competitive markets do not account for negative externalities; indirect costs that some participants impose on others, such as the cost of over-appropriating a common-p…
Improved Cooperation by Exploiting a Common Signal
Panayiotis Danassis, Zeki Doruk Erden, Boi Faltings
Can artificial agents benefit from human conventions? Human societies manage to successfully self-organize and resolve the tragedy of the commons in common-pool resources, in spite…
A Distributed Differentially Private Algorithm for Resource Allocation in Unboundedly Large Settings
Panayiotis Danassis, Aleksei Triastcyn, Boi Faltings
We introduce a practical and scalable algorithm (PALMA) for solving one of the fundamental problems of multi-agent systems -- finding matches and allocations -- in unboundedly larg…
Putting Ridesharing to the Test: Efficient and Scalable Solutions and the Power of Dynamic Vehicle Relocation
Panayiotis Danassis, Marija Sakota, Aris Filos-Ratsikas +1
We study the optimization of large-scale, real-time ridesharing systems and propose a modular design methodology, Component Algorithms for Ridesharing (CAR). We evaluate a diverse…
Anytime Heuristic for Weighted Matching Through Altruism-Inspired Behavior
Panayiotis Danassis, Aris Filos-Ratsikas, Boi Faltings
We present a novel anytime heuristic (ALMA), inspired by the human principle of altruism, for solving the assignment problem. ALMA is decentralized, completely uncoupled, and requi…
Courtesy as a Means to Coordinate
Panayiotis Danassis, Boi Faltings
We investigate the problem of multi-agent coordination under rationality constraints. Specifically, role allocation, task assignment, resource allocation, etc. Inspired by human be…