Y
Ya'akov Gal
Researcher at Ben-Gurion University of the Negev
Publications - 92
Citations - 2268
Ya'akov Gal is an academic researcher from Ben-Gurion University of the Negev. The author has contributed to research in topics: Negotiation & Computer science. The author has an hindex of 24, co-authored 84 publications receiving 2031 citations. Previous affiliations of Ya'akov Gal include Massachusetts Institute of Technology & Harvard University.
Papers
More filters
Proceedings ArticleDOI
Modeling User Perception of Interaction Opportunities for Effective Teamwork
TL;DR: Results show that the magnitude of the benefit of interruption to the collaboration is a major factor influencing the likelihood that people will accept interruption requests and imply that system designers need to consider not only the possible benefits of interruptions to collaborative human-computer teams but also the way that such benefits are perceived by people.
Journal ArticleDOI
When Time is Not Money: Why Americans May Lose Out at the Negotiation Table
TL;DR: Although previous research has linked hyperbolic discounting, an economic model of impatience, to negative outcomes such as smoking, problem drinking, lowered academic achievement, and ineffective....
Book ChapterDOI
Towards Collaborative Intelligent Tutors: Automated Recognition of Users' Strategies
TL;DR: The algorithm presented in this paper decomposes students' complete interaction histories with the software into hierarchies of interdependent tasks that may be subsequently compared with ideal solutions.
Journal ArticleDOI
Humancomputer negotiation in a three player market setting
TL;DR: This work shows that for particular market settings involving competition between service providers, equilibrium strategies can be a successful design paradigm for computer agents without relying on data driven approaches.
Journal ArticleDOI
Behavioral Study of Users When Interacting with Active Honeytokens
TL;DR: The results of the first study indicate that it is possible to automatically generate honeytokens that are difficult for users to distinguish from real tokens and can inform security system designers about the type of environmental variables that affect people's data misuse behavior and how to generate honey takens that evade detection.