no code implementations • ICML 2020 • Elad Sarafian, Mor Sinay, yoram louzoun, Noa Agmon, Sarit Kraus
We prove the convergence of EGL to a stationary point and its robustness in the optimization of integrable functions.
no code implementations • 20 Apr 2024 • Xiaoli Tang, Han Yu, Xiaoxiao Li, Sarit Kraus
To enhance the efficiency in AFL decision support for stakeholders (i. e., data consumers, data owners, and the auctioneer), intelligent agent-based techniques have emerged.
no code implementations • 28 Jan 2024 • Anat Hashavit, Tamar Stern, Hongning Wang, Sarit Kraus
These results strongly suggest that an information need-focused approach can significantly improve the reliability of extracted snippets in online health search.
1 code implementation • 28 Aug 2023 • Jonathan Shaki, Sarit Kraus, Michael Wooldridge
Large Language Models (LLMs) such as ChatGPT have received enormous attention over the past year and are now used by hundreds of millions of people every day.
no code implementations • 11 Aug 2023 • Parisa Zehtabi, Alberto Pozanco, Ayala Bloch, Daniel Borrajo, Sarit Kraus
We propose CMAoE, a domain-independent approach to obtain contrastive explanations by: (i) generating a new solution $S^\prime$ where property $P$ is enforced, while also minimizing the differences between $S$ and $S^\prime$; and (ii) highlighting the differences between the two solutions, with respect to the features of the objective function of the multi-agent system.
1 code implementation • 17 May 2023 • Kayla Boggess, Sarit Kraus, Lu Feng
As multi-agent reinforcement learning (MARL) systems are increasingly deployed throughout society, it is imperative yet challenging for users to understand the emergent behaviors of MARL agents in complex environments.
2 code implementations • 29 Apr 2023 • Gideon Freund, Elad Sarafian, Sarit Kraus
In reinforcement learning and imitation learning, an object of central importance is the state distribution induced by the policy.
1 code implementation • 30 Nov 2022 • Yohai Trabelsi, Abhijin Adiga, Sarit Kraus, S. S. Ravi, Daniel J. Rosenkrantz
For a general class of benefit functions satisfying certain properties (including diminishing returns), we show that this multi-round matching problem is efficiently solvable.
no code implementations • 31 Oct 2022 • Peter Stone, Rodney Brooks, Erik Brynjolfsson, Ryan Calo, Oren Etzioni, Greg Hager, Julia Hirschberg, Shivaram Kalyanakrishnan, Ece Kamar, Sarit Kraus, Kevin Leyton-Brown, David Parkes, William Press, AnnaLee Saxenian, Julie Shah, Milind Tambe, Astro Teller
In September 2016, Stanford's "One Hundred Year Study on Artificial Intelligence" project (AI100) issued the first report of its planned long-term periodic assessment of artificial intelligence (AI) and its impact on society.
no code implementations • 12 Sep 2022 • Yaniv Oshrat, Yonatan Aumann, Tal Hollander, Oleg Maksimov, Anita Ostroumov, Natali Shechtman, Sarit Kraus
The prospect of combining human operators and virtual agents (bots) into an effective hybrid system that provides proper customer service to clients is promising yet challenging.
1 code implementation • 12 Sep 2022 • Yohai Trabelsi, Abhijin Adiga, Sarit Kraus, S. S. Ravi
Our focus is on resource allocation problems where agents may have restrictions that make them incompatible with some resources.
no code implementations • 10 Jul 2022 • Anat Hashavit, Hongning Wang, Tamar Stern, Sarit Kraus
We further discover that the contrast between the indirect marketing ads and the viewpoint presented in the organic search results plays an important role in users' decision-making.
no code implementations • 24 May 2022 • Sharadhi Alape Suryanarayana, David Sarne, Sarit Kraus
In many social-choice mechanisms the resulting choice is not the most preferred one for some of the participants, thus the need for methods to justify the choice made in a way that improves the acceptance and satisfaction of said participants.
no code implementations • 29 Apr 2022 • Dolev Mutzari, Yonatan Aumann, Sarit Kraus
In this paper, we introduce a robust model for MSSGs, which admits solutions that are resistant to small perturbations or uncertainties in the game's parameters.
1 code implementation • 26 Apr 2022 • Kayla Boggess, Sarit Kraus, Lu Feng
Advances in multi-agent reinforcement learning (MARL) enable sequential decision making for a range of exciting multi-agent applications such as cooperative AI and autonomous driving.
no code implementations • 16 Mar 2022 • Alberto Pozanco, Francesca Mosca, Parisa Zehtabi, Daniele Magazzeni, Sarit Kraus
The EXPRES framework consists of: (i) an explanation generator that, based on a Mixed-Integer Linear Programming model, finds the best set of reasons that can explain an unsatisfied preference; and (ii) an explanation parser, which translates the generated explanations into human interpretable ones.
1 code implementation • 3 Mar 2022 • Mor Sinay, Noa Agmon, Oleg Maksimov, Aviad Fux, Sarit Kraus
We suggest a real-time algorithmic framework for the UAVs, combining entropy and stochastic-temporal belief, that aims at optimizing the probability of a quick and successful detection of all of the targets.
1 code implementation • 12 Jun 2021 • Shai Keynan, Elad Sarafian, Sarit Kraus
In particular, the input of the Q-function is both the state and the action, and in multi-task problems (Meta-RL) the policy can take a state and a context.
no code implementations • 9 May 2021 • Aviram Aviv, Yaniv Oshrat, Samuel A. Assefa, Tobi Mustapha, Daniel Borrajo, Manuela Veloso, Sarit Kraus
Call centers, in which human operators attend clients using textual chat, are very common in modern e-commerce.
no code implementations • 4 May 2021 • Guy Barash, Eitan Farchi, Sarit Kraus, Onn Shehory
We show that, with a low attack budget, our attack's success rate is above 80%, and in some cases 100%, for white-box learning.
no code implementations • 31 Dec 2020 • Erfan Pakdamanian, Shili Sheng, Sonia Baee, Seongkook Heo, Sarit Kraus, Lu Feng
Nevertheless, automated vehicles may still need to occasionally hand the control back to drivers due to technology limitations and legal requirements.
no code implementations • 9 Jun 2020 • Mor Sinay, Elad Sarafian, yoram louzoun, Noa Agmon, Sarit Kraus
Instead of fitting the function, EGL trains a NN to estimate the objective gradient directly.
no code implementations • 10 Oct 2019 • Sarit Kraus, Amos Azaria, Jelena Fiosina, Maike Greve, Noam Hazon, Lutz Kolbe, Tim-Benjamin Lembcke, Jörg P. Müller, Sören Schleibaum, Mark Vollrath
Explanation is necessary for humans to understand and accept decisions made by an AI system when the system's goal is known.
no code implementations • 27 Sep 2018 • Elad Sarafian, Aviv Tamar, Sarit Kraus
The primary advantages of our approach, termed Rerouted Behavior Improvement (RBI), over other safe learning methods are its stability in the presence of value estimation errors and the elimination of a policy search process.
no code implementations • 3 Jul 2018 • Akiva Kleinerman, Ariel Rosenfeld, Sarit Kraus
These platforms often include recommender systems that assist users in finding a suitable match.
1 code implementation • 20 May 2018 • Elad Sarafian, Aviv Tamar, Sarit Kraus
To minimize the improvement penalty, the RBI idea is to attenuate rapid policy changes of low probability actions which were less frequently sampled.
no code implementations • 15 May 2018 • Ariel Rosenfeld, Moshe Cohen, Matthew E. Taylor, Sarit Kraus
However, injecting human knowledge into an RL agent may require extensive effort and expertise on the human designer's part.
no code implementations • 19 Jun 2017 • Hanan Rosemarin, John P. Dickerson, Sarit Kraus
The use of semi-autonomous and autonomous robotic assistants to aid in care of the elderly is expected to ease the burden on human caretakers, with small-stage testing already occurring in a variety of countries.
no code implementations • 24 Jun 2016 • Sarit Kraus
In this paper we will consider the question of whether strategies implied by theories of strategic behavior can be used by automated agents that interact proficiently with people.
no code implementations • 31 May 2016 • Moshe Bitan, Galit Nahari, Zvi Nisin, Ariel Roth, Sarit Kraus
In this paper, we present a Virtual-Suspect system which can be used to train inexperienced law enforcement personnel in interrogation strategies.
no code implementations • 20 Feb 2014 • Sigal Sina, Sarit Kraus, Avi Rosenfeld
We found that the generated scenarios were rated as reliable and consistent by the crowd when compared to the scenarios that were originally captured.