Explaining Ridesharing: Selection of Explanations for Increasing User Satisfaction

פרסום מחקרי: פרק בספר / בדוח / בכנספרסום בספר כנסביקורת עמיתים

3 ציטוטים ‏(Scopus)

תקציר

Transportation services play a crucial part in the development of modern smart cities. In particular, on-demand ridesharing services, which group together passengers with similar itineraries, are already operating in several metropolitan areas. These services can be of significant social and environmental benefit, by reducing travel costs, road congestion and CO2 emissions. Unfortunately, despite their advantages, not many people opt to use these ridesharing services. We believe that increasing the user satisfaction from the service will cause more people to utilize it, which, in turn, will improve the quality of the service, such as the waiting time, cost, travel time, and service availability. One possible way for increasing user satisfaction is by providing appropriate explanations comparing the alternative modes of transportation, such as a private taxi ride and public transportation. For example, a passenger may be more satisfied from a shared-ride if she is told that a private taxi ride would have cost her 50% more. Therefore, the problem is to develop an agent that provides explanations that will increase the user satisfaction. We model our environment as a signaling game and show that a rational agent, which follows the perfect Bayesian equilibrium, must reveal all of the information regarding the possible alternatives to the passenger. In addition, we develop a machine learning based agent that, when given a shared-ride along with its possible alternatives, selects the explanations that are most likely to increase user satisfaction. Using feedback from humans we show that our machine learning based agent outperforms the rational agent and an agent that randomly chooses explanations, in terms of user satisfaction.

שפה מקוריתאנגלית
כותר פרסום המארחMulti-Agent Systems - 18th European Conference, EUMAS 2021, Revised Selected Papers
עורכיםAriel Rosenfeld, Nimrod Talmon
מוציא לאורSpringer Science and Business Media Deutschland GmbH
עמודים89-107
מספר עמודים19
מסת"ב (מודפס)9783030822538
מזהי עצם דיגיטלי (DOIs)
סטטוס פרסוםפורסם - 2021
אירוע18th European Conference on Multi-Agent Systems, EUMAS 2021 - Virtual, Online
משך הזמן: 28 יוני 202129 יוני 2021

סדרות פרסומים

שםLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
כרך12802 LNAI
ISSN (מודפס)0302-9743
ISSN (אלקטרוני)1611-3349

כנס

כנס18th European Conference on Multi-Agent Systems, EUMAS 2021
עירVirtual, Online
תקופה28/06/2129/06/21

טביעת אצבע

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