Selected Publications

Online prediction of time series with
assumed behavior

Published:   2020/2/1   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 in 

Are drivers ready for traffic enforcement drones?

Published:   2019/1/1   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 challenge

Optimal cruiser-drone traffic enforcement
under energy limitation

Published:   2019/12/1   By:   Ariel Rosenfeld,   Oleg Maksimov

Drones can assist in mitigating traffic accidents by deterring reckless drivers, leveraging their flexible mobility. In the real-world, drones are fundamentally limited by their

Emergency department online patient-
caregiver scheduling

Published:   2019/7/21   By:   Ariel Rosenfeld,   Hanan Rosemarin,   Sarit Kraus

Emergency Departments (EDs) provide an imperative source of medical care. Central to the ED workflow is the patientcaregiver scheduling, directed at getting the right patient to

Big data analytics and ai in mental healthcare

Published:   2019/3/12   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

Labor Division with Movable Walls: Composing Executable Specifications with Machine Learning and Search (Blue Sky Idea)

Published:   2019/7/17   By:   Ariel Rosenfeld,   David Harel,   Assaf Marron,   Moshe Vardi,   Gera Weiss

Artificial intelligence (AI) techniques, including, eg, machine learning, multi-agent collaboration, planning, and heuristic search, are emerging as ever-stronger tools for

Playing Chess at a Human Desired
Level and Style

Published:   2019/9/25   By:   Ariel Rosenfeld,   Hanan Rosemarin

Human chess players prefer training with human opponents over chess agents as the latter are distinctively different in level and style than humans. Chess agents designed 

Human-Agent Interaction for Human Space Exploration

Published:   2019/6/6   By:   Ariel Rosenfeld

Human space exploration creates unique challenges and opportunities for many scientific disciplines. From the human-agent interaction perspective, these require 

Labor Division with Movable Walls: Composing Executable Specifications with Machine Learning and Search

Published:   2019   By:   Ariel Rosenfeld,   David Harel,   Assaf Marron,   Moshe Vardi,   Gera Weiss

Artificial intelligence (AI) techniques, including, eg, machine learning, multi-agent collaboration, planning, and heuristic search, are emerging as ever-stronger tools for

Predicting human decision-making:
From prediction to action‏

Published:   2018/1/22   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

Leveraging human knowledge in tabular reinforcement learning: A study of human subjects‏

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

Providing explanations for recommendations in reciprocal environments

Published: 2018/9/27   By:   Ariel Rosenfeld,   Akiva Kleinerman,   Sarit Kraus

Automated platforms which support users in finding a mutually beneficial match, such as online dating and job recruitment sites, are becoming increasingly popular.

Optimally balancing receiver and recommended users' importance in reciprocal recommender systems

Published: 2018/9/27   By:   Ariel Rosenfeld,   Akiva Kleinerman,   Francesco Ricci,   Sarit Kraus

Automated platforms which support users in finding a mutually beneficial match, such as online dating and job recruitment sites, are becoming increasingly popular.

Automation of android applications functional testing using machine learning activities classification

Published:   2018/5/27   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

Published:   2018   By:   Ariel Rosenfeld,   David Benrimoh,   Robert Fratila,   Sonia Israel,   Kelly Perlman,   Nykan Mirchi,   Sneha Desai,   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 treatment selection

From Psychological Persuasion To Abstract Argumentation: A Step Forward

Published:   2018/4/6   By:   Ariel Rosenfeld,   Jean-Baptiste Corrégé,   Emmanuel Hadoux

Developing argumentation-based persuasive agents that leverage human argumentative techniques is an open challenge in the computational argumentation field.

Predicting Human Decision-Making: From Prediction to Action, Ariel Rosenfeld, Sarit Kraus, Morgan & Claypool Publishers (2018)

Published:  2018/10/1   By:   Ariel Rosenfeld,   Sarit Kraus, Bo an לבדוק

The last few years have witnessed significant AI research progress in many domains including vision, natural language processing, security, and games such as Go and Poker.

Strategic Human-Agent Interaction: From Promoting Traffic Safety to Search and Rescue

Published:   2018/7/9   By:   Ariel Rosenfeld

The last few years have witnessed significant AI research progress in many domains including vision, natural language processing, security, and games such as Go and Poker.

When Security Games Hit Traffic: Optimal Traffic Enforcement Under One Sided Uncertainty.

Published:  2017/8/19   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

Optimizing traffic enforcement:
From the lab to the roads

Published:  2017/10/23   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

Automation of Android Applications Testing Using Machine Learning Activities Classification

Published:   2017/9/4   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. With the increasingly widespread usage

Speeding up tabular reinforcement learning using state-action similarities

Published:   2017/5/8   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

ACAT: a novel machine-learning-based tool for automating Android application testing

Published:   2017/11/13   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. With the increasingly widespread usage

Multiple Robots For Multiple Missions: Architecture for Complex Collaboration

Published:   2017   By:   Ariel Rosenfeld,   Noa Agmon,   Oleg Maximov,   Shai Shlomai,   Sarit Kraus

As systems of multiple robots become more prevalent both in research and in real world applications, they may be required to handle new missions, collaborate in teams

Strategical argumentative agent for human persuasion

Published:   2016/8/29   By:   Ariel Rosenfeld,   Sarit Kraus,

Automated agents should be able to persuade people in the same way people persuade each other-via dialogs. Today, automated persuasion modeling and research

A pilot study in using argumentation frameworks for online debates

Published:   2016/8/31   By:   Ariel Rosenfeld,   Federico Cerutti,   Alexis Palmer,   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. This pilot study aims at exploring

Online prediction of exponential decay time series with human-agent application

Published:  2016/8/29   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

Human-multi-robot team collaboration for efficent warehouse operation

Published:   2016   By:   Ariel Rosenfeld,   A Noa,   O Maksimov,   S Kraus

Multi-robot systems have been successfully deployed in modern warehouses where they are required to move merchandise and equipment from one place to another.

Strategical argumentative agent for human persuasion: A preliminary report

Published:   2016/4/17   By:   Ariel Rosenfeld,   Sarit Kraus

Automated agents should be able to persuade people in the same way people persuade each other, namely via dialog. Today, automated persuasion modeling and investigation

Human-Multi-Robot Team Collaboration using Advising Agents: (Doctoral Consortium)

Published:   2016/5/9   By:   Ariel Rosenfeld

The number of multi-robot systems deployed in field applications has risen dramatically over the years. Nevertheless, the part of the human operator in these systems

3.20 Strategical Argumentative Agent for Human Persuasion‏

Published:   2016   By:   Ariel Rosenfeld

Automated agents should be able to persuade people in the same way people persuade each other–via dialogs. Today, automated persuasion modeling and research

חסר קישור

Providing Arguments in Discussions Based on the Prediction of Human Argumentative Behavior‏

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 for developing agents

Intelligent Agent Supporting Human-Multi-Robot Team Collaboration⋆

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

Advice provision for energy saving in automobile climate-control system

Published:   2015/9/28   By:   Ariel Rosenfeld,  Amos Azaria,   Sarit Kraus,   Claudia V Goldman,   Omer Tsimhoni

Reducing energy consumption of climate control systems is important in order to reduce human environmental footprint. The need to save energy becomes even greater

Adaptive advice in automobile climate
control systems

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

Automated agents for advice provision

Published:   2015/6/27     By:   Ariel Rosenfeld

In this thesis, we focus on automated advising agents. The advice given is a form of relating recommendations or guidance from an automated agent to its human user.

Argumentation Theory in the Field: An Empirical Study of Fundamental Notions

Published:   2014   By:   Ariel Rosenfeld,   Sarit Kraus

Argumentation Theory provides a very powerful set of principles, ideas and models. Yet, in this paper we will show that its fundamental principles unsatisfactorily

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