An automated meeting scheduling system that utilizes user preferences

Haynes, Thomas; Sen, Sandip; Arora, Neeraj; Nadella, Rajani

doi:10.1145/267658.267733

Cited by 39 publications

(16 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Other works aimed to leverage the strengths of both humans and machines in scheduling by soliciting user input in the form of quantitative, qualitative, hard or soft constraints over various scheduling options. Recommended schedules were then autonomously compiled and provided to users [3], [16], [17], [22], [32]. While developed to support scheduling of human teams, these approaches can be readily extended to human-robot teams.…”

Section: Introductionmentioning

confidence: 99%

Decision-Making Authority, Team Efficiency and Human Worker Satisfaction in Mixed Human-Robot Teams

Gombolay

Gutierrez

Sturla

et al. 2014

Robotics: Science and Systems X

View full text Add to dashboard Cite

Abstract-In manufacturing, advanced robotic technology has opened up the possibility of integrating highly autonomous mobile robots into human teams. However, with this capability comes the issue of how to maximize both team efficiency and the desire of human team members to work with robotic counterparts. We hypothesized that giving workers partial decision-making authority over a task allocation process for the scheduling of work would achieve such a maximization, and conducted an experiment on human subjects to test this hypothesis. We found that an autonomous robot can outperform a worker in the execution of part or all of the task allocation (p < 0.001 for both). However, rather than finding an ideal balance of control authority to maximize worker satisfaction, we observed that workers preferred to give control authority to the robot (p < 0.001). Our results indicate that workers prefer to be part of an efficient team rather than have a role in the scheduling process, if maintaining such a role decreases their efficiency. These results provide guidance for the successful introduction of semi-autonomous robots into human teams.

show abstract

Section: Introductionmentioning

confidence: 99%

Decision-Making Authority, Team Efficiency and Human Worker Satisfaction in Mixed Human-Robot Teams

Gombolay

Gutierrez

Sturla

et al. 2014

Robotics: Science and Systems X

View full text Add to dashboard Cite

show abstract

“…Ghosh et al [15] built a movie recommendation system; a user's preferences were represented as agents, and movies to be suggested were selected through agent voting. Candidates in virtual elections have also been beliefs, joint plans [10], and schedules [17].…”

Section: Introductionmentioning

confidence: 99%

Power in threshold network flow games

Bachrach

Rosenschein

2008

Auton Agent Multi-Agent Syst

View full text Add to dashboard Cite

Preference aggregation is used in a variety of multiagent applications, and as a result, voting theory has become an important topic in multiagent system research. However, power indices (which reflect how much "real power" a voter has in a weighted voting system) have received relatively little attention, although they have long been studied in political science and economics. We consider a particular multiagent domain, a threshold network flow game. Agents control the edges of a graph; a coalition wins if it can send a flow that exceeds a given threshold from a source vertex to a target vertex. The relative power of each edge/agent reflects its significance in enabling such a flow, and in real-world networks could be used, for example, to allocate resources for maintaining parts of the network. We examine the computational complexity of calculating two prominent power indices, the Banzhaf index and the Shapley-Shubik index, in this network flow domain. We also consider the complexity of calculating the core in this domain. The core can be used to allocate, in a stable manner, the gains of the coalition that is established. We show that calculating the Shapley-Shubik index in this network flow domain is NP-hard, and that calculating the Banzhaf index is #P-complete. Despite these negative results, we show that for some restricted network flow domains there exists a polynomial algorithm for calculating agents' Banzhaf power indices. We also show that computing the core in this game can be performed in polynomial time.

show abstract

“…The candidates in the election can be beliefs, plans (Ephrati & Rosenschein, 1997), schedules (Haynes, Sen, Arora, & Nadella, 1997), or indeed many other less obvious entities, such as movies (Ghosh, Mundhe, Hernandez, & Sen, 1999). Applications of voting, in place of other methods, are motivated by theoretical guarantees provided by various voting protocols.…”

Section: Introductionmentioning

confidence: 99%

Junta Distributions and the Average-Case Complexity of Manipulating Elections

Procaccia¹,

Rosenschein²

2007

jair

View full text Add to dashboard Cite

Encouraging voters to truthfully reveal their preferences in an election has long been an important issue. Recently, computational complexity has been suggested as a means of precluding strategic behavior. Previous studies have shown that some voting protocols are hard to manipulate, but used N P-hardness as the complexity measure. Such a worst-case analysis may be an insufficient guarantee of resistance to manipulation.Indeed, we demonstrate that N P-hard manipulations may be tractable in the averagecase. For this purpose, we augment the existing theory of average-case complexity with some new concepts. In particular, we consider elections distributed with respect to junta distributions, which concentrate on hard instances. We use our techniques to prove that scoring protocols are susceptible to manipulation by coalitions, when the number of candidates is constant.

show abstract

An automated meeting scheduling system that utilizes user preferences

Cited by 39 publications

References 8 publications

Decision-Making Authority, Team Efficiency and Human Worker Satisfaction in Mixed Human-Robot Teams

Decision-Making Authority, Team Efficiency and Human Worker Satisfaction in Mixed Human-Robot Teams

Power in threshold network flow games

Junta Distributions and the Average-Case Complexity of Manipulating Elections

Contact Info

Product

Resources

About