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Selected Publications
Too Smart for Their Own Good: Trading Trufulness for Efficiency in the Israeli Medical Internship Market
Judgment and Decision Making (JDM)
Published: 2020 By: Ariel Rosenfeld, Avinatan Hassidim
In this article, we investigate this trade-off through the high-stakes Israeli medical internship market.
Supporting Users in Finding Successful Matches in Reciprocal Recommender Systems
User Modeling and User-Adapted Interaction (UMUAI)
Published: 2020 By: Akiva Kleinerman, Ariel Rosenfeld, Sarit Kraus and Francesco Ricci.
Generating successful recommendations in such systems is challenging as the system must balance two objectives: (1) recommending users with whom the recommendation receiver is likely to initiate an interaction and (2) recommending users who are likely to reply positively to the recommendation receiver initiated interaction. Unfortunately, these objectives are partially conflicting…
When Security Games Hit Traffic: A Deployed Optimal Traffic Enforcement System
Artificial Intelligence Journal (AIJ)
Published: 2020 By: Ariel Rosenfeld, Oleg Maksimov, Sarit Kraus.
In this article, we present a novel model, an optimizing algorithm and a deployed system which together mitigate many of the computational and real-world challenges of traffic enforcement allocation in large road networks.
Online prediction of time series with
assumed behavior
Engineering Applications of Artificial Intelligence.
Published: 2020 By: Ariel Rosenfeld, Moshe Cohen, Sarit Kraus, Joseph Keshet
The prediction of future time series values is essential for many fields and applications. In some settings, the time series behavior is expected to follow distinct patterns which can be used…
Are drivers ready for traffic enforcement drones?
Accident Analysis & Prevention.
Published: 2019 By: Ariel Rosenfeld
Traffic enforcement drones reduce high-risk driving behavior which often leads to traffic crashes. However, the introduction of drones may face a public acceptance challenges…
Optimal cruiser-drone traffic enforcement
under energy limitation
Artificial Intelligence Journal (AIJ).
Published: 2019 By: Ariel Rosenfeld, Oleg Maksimov
Drones can assist in mitigating traffic accidents by deterring reckless drivers, leveraging their flexible mobility. However, in the real-world, drones are fundamentally limited …
Emergency department online patient-
caregiver scheduling
AAAI
Published: 2019 By: Hanan Rosemarin, Ariel Rosenfeld Sarit Kraus
Emergency Departments (EDs) provide an imperative source of medical care. Central to the ED workflow is the patient-caregiver scheduling, which is highly complex.
Big data analytics and AI in mental healthcare
Published: 2019 By: Ariel Rosenfeld, David Benrimoh, Caitrin Armstrong, Nykan Mirchi, Timothe Langlois-Therrien, Colleen Rollins, Myriam Tanguay-Sela, Joseph Mehltretter, Robert Fratila, Sonia Israel, Emily Snook, Kelly Perlman, Akiva Kleinerman, Bechara Saab, Mark Thoburn, Cheryl Gabbay, Amit Yaniv-Rosenfel
Mental health conditions cause a great deal of distress or impairment; depression alone will affect 11% of the world’s population. The application of Artificial Intelligence can significantly help.
Labor Division with Movable Walls: Composing Executable Specifications with Machine Learning and Search (Blue Sky Idea)
AAAI
Published: 2019 By: David Harel, Assaf Marron, Moshe Vardi, Ariel Rosenfeld, Gera Weiss
Artificial intelligence (AI) techniques can go hand in hand with Executable Specifications.
Playing Chess at a Human Desired
Level and Style
HAI
Published: 2019 By: Hanan Rosemarin Ariel Rosenfeld,
Human chess players prefer training with human opponents over chess agents as the latter are distinctively different in level and style than humans. Can we fill the gap?
Human-Agent Interaction for Human Space Exploration
UMAP
Published: 2019 By: Ariel Rosenfeld
Human space exploration creates unique challenges and opportunities for many scientific disciplines. From the human-agent interaction perspective, here are a few…
Predicting human decision-making:
From prediction to action
Published: 2018 By: Ariel Rosenfeld, Sarit Kraus
Human decision-making often transcends our formal models of “rationality.” Designing intelligent agents that interact proficiently with people necessitates the modeling of their deicsions…
Leveraging human knowledge in tabular reinforcement learning: A study of human subjects
KER
Published: 2018 By: Ariel Rosenfeld, Moshe Cohen, Matthew E Taylor, Sarit Kraus
Reinforcement learning (RL) can be extremely effective in solving complex, real-world problems. However, injecting human knowledge into an RL agent may require extensive experience…
Providing explanations for recommendations in reciprocal environments
RecSys
Published: 2018 By: Akiva Kleinerman, Ariel Rosenfeld, Sarit Kraus
Automated platforms which support users in finding a mutually beneficial match, such as online dating and job recruitment sites, require different explnations than regular ones do…
Optimally balancing receiver and recommended users' importance in reciprocal recommender systems
RecSys
Published: 2018 By: Akiva Kleinerman, Ariel Rosenfeld, Francesco Ricci, Sarit Kraus
Automated platforms which support users in finding a mutually beneficial match, such as online dating and job recruitment sites, require some form of balancing between the receiver and the recommended user’s interests…
Automation of android applications functional testing using machine learning activities classification
MobileSoft
Published: 2018 By: Ariel Rosenfeld, Odaya Kardashov, Orel Zang
Following the ever-growing demand for mobile applications, researchers are constantly developing new test automation solutions for mobile developers. However, researchers
Aifred Health, a Deep Learning Powered Clinical Decision Support System for Mental Health
NIPS
Published: 2018 By: David Benrimoh, Robert Fratila, Sonia Israel, Kelly Perlman, Nykan Mirchi, Sneha Desai, Ariel Rosenfeld, Sabrina Knappe, Jason Behrmann, Colleen Rollins, Raymond Penh You
Aifred Health, one of the top two teams in the first round of the IBM Watson AI XPRIZE competition, is using deep learning to solve the problem of depression treatment selection
Automation of android applications functional testing using machine learning activities classification
MobileSoft
Published: 2018 By: Ariel Rosenfeld, Odaya Kardashov, Orel Zang
Following the ever-growing demand for mobile applications, researchers are constantly developing new test automation solutions for mobile developers. However, researchers
When Security Games Hit Traffic: Optimal Traffic Enforcement Under One Sided Uncertainty.
IJCAI
Published: 2017 By: Ariel Rosenfeld, Sarit Kraus
Efficient traffic enforcement is an essential, yet complex, component in preventing road accidents. In this paper, we present a novel model and an optimizing algorithm to that end.
Optimizing traffic enforcement:
From the lab to the roads
GameSec
Published: 2017 By: Ariel Rosenfeld, Oleg Maksimov, Sarit Kraus
Road accidents are the leading causes of death of youths and young adults worldwide. Efficient traffic enforcement has been conclusively shown to reduce high-risk
Speeding up tabular reinforcement learning using state-action similarities
Published: 2017 By: Ariel Rosenfeld, Matthew E Taylor, Sarit Kraus
One of the most prominent approaches for speeding up reinforcement learning is injecting human prior knowledge into the learning agent. This paper proposes a novel to that end.
ACAT: a novel machine-learning-based tool for automating Android application testing
HVC
Published: 2017 By: Ariel Rosenfeld, Odaya Kardashov, Orel Zang
Mobile applications are being used every day by more than half of the world’s population to perform a great variety of tasks. Can machine learning be used to automatically test them?
Strategical argumentative agent for human persuasion
ECAI
Published: 2016 By: Ariel Rosenfeld, Sarit Kraus,
Automated agents should be able to persuade people in the same way people persuade each other-via dialogs. Here is the first attempt to do so.
A pilot study in using argumentation frameworks for online debates
Published: 2016 By: Federico Cerutti, Alexis Palmer, Ariel Rosenfeld, Jan Šnajder, Francesca Toni
We describe a pilot study in using argumentation frameworks obtained from an online debate to evaluate positions expressed in the debate.
Online prediction of exponential decay time series with human-agent application
ECAI
Published: 2016 By: Ariel Rosenfeld, Joseph Keshet, Claudia V Goldman, Sarit Kraus
Exponential decay time series are prominent in many fields. In some applications, the time series behavior can change over time due to a change in the user’s preferences
Providing Arguments in Discussions Based on the Prediction of Human Argumentative Behavior
AAAI
Published: 2015 By: Ariel Rosenfeld, Sarit Kraust
Argumentative discussion is a highly demanding task. In order to help people in such discussions, this article provides an innovative methodology…
Intelligent Agent Supporting Human-Multi-Robot Team Collaboration
IJCAI
Published: 2015 By: Ariel Rosenfeld, Noa Agmon, Oleg Maksimov, Amos Azaria, Sarit Kraus
The number of multi-robot systems deployed in field applications has risen dramatically over the years. Nevertheless, supervising and operating multiple robots can be hard…
Advice provision for energy saving in automobile climate-control system
AI Magazine
Published: 2015 By: Amos Azaria, Ariel Rosenfeld, Sarit Kraus, Claudia V Goldman, Omer Tsimhoni
AI for saving energy in automobile climate control system.
Adaptive advice in automobile climate
control systems
AAMAS
Published: 2015 By: Ariel Rosenfeld, Amos Azaria, Sarit Kraus, Claudia V Goldman, Omer Tsimhoni
Reducing an automobile’s energy consumption will lower its dependency on fossil fuel and extend the travel range of electric vehicles. Automobile Climate Control Systems consume a lot…