Search Results for author: Yoav Kolumbus

Found 6 papers, 1 papers with code

Contracting with a Learning Agent

no code implementations29 Jan 2024 Guru Guruganesh, Yoav Kolumbus, Jon Schneider, Inbal Talgam-Cohen, Emmanouil-Vasileios Vlatakis-Gkaragkounis, Joshua R. Wang, S. Matthew Weinberg

We initiate the study of repeated contracts with a learning agent, focusing on agents who achieve no-regret outcomes.

Explainable Reinforcement Learning via Model Transforms

1 code implementation24 Sep 2022 Mira Finkelstein, Lucy Liu, Nitsan Levy Schlot, Yoav Kolumbus, David C. Parkes, Jeffrey S. Rosenshein, Sarah Keren

This has given rise to a variety of approaches to explainability in RL that aim to reconcile discrepancies that may arise between the behavior of an agent and the behavior that is anticipated by an observer.

Decision Making reinforcement-learning +1

How and Why to Manipulate Your Own Agent: On the Incentives of Users of Learning Agents

no code implementations14 Dec 2021 Yoav Kolumbus, Noam Nisan

The usage of automated learning agents is becoming increasingly prevalent in many online economic applications such as online auctions and automated trading.

Auctions Between Regret-Minimizing Agents

no code implementations22 Oct 2021 Yoav Kolumbus, Noam Nisan

We analyze a scenario in which software agents implemented as regret-minimizing algorithms engage in a repeated auction on behalf of their users.

Neural Networks for Predicting Human Interactions in Repeated Games

no code implementations8 Nov 2019 Yoav Kolumbus, Gali Noti

We show that if the available input is only of a short sequence of play, economic information about the game is important for predicting behavior of human agents.

Behavior-Based Machine-Learning: A Hybrid Approach for Predicting Human Decision Making

no code implementations30 Nov 2016 Gali Noti, Effi Levi, Yoav Kolumbus, Amit Daniely

A large body of work in behavioral fields attempts to develop models that describe the way people, as opposed to rational agents, make decisions.

BIG-bench Machine Learning Decision Making

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