An agent-based approach to solve dynamic meeting scheduling problems with preferences

Benhassine, Ahlem; Ho, Tu Bao

doi:10.1016/j.engappai.2006.10.004

Cited by 33 publications

(26 citation statements)

References 14 publications

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“…This work can be considered as the first version of the proposed approach. The integration of the dynamic process was presented in [4] where the proposed protocol focused on maximizing the utility of all the agents of the system.…”

Section: Global Ms Dynamicmentioning

confidence: 99%

Meetings scheduling solver enhancement with local consistency reinforcement

Hassine

Ito

2006

Appl Intell

Self Cite

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Meeting scheduling (MS) represents an important real-world group decision application that denotes one of the actual combinatorial problems. Solving this problem consists of scheduling all the meetings while satisfying all the constraints related to both the users and the meetings. However, given human nature, the solution is usually delineated by the encountering of conflicting preferences. Most of existing research efforts allow the relaxation of the users' preferences in order to reach an agreement between all the participants, which is not always possible. In addition, they do not deal with the achievement of any level of local consistency to enhance the efficiency of the solving process, and finally, they do not address the real difficulty of distributed systems, which is the complexity of message passing operations.Here we propose a new approach to facilitate and streamline the scheduling meetings process in any organization. This approach is based on the distributed reinforcement of arc consistency model, which takes into account the difficulties mentioned above. The present work focuses mainly on satisfying meetings hosts' preferences as much as possible, while taking into consideration all users' availability. The underlying selfish protocol is able to efficiently reach the best solution for the host of the meeting (according to the predefined criteria) whenever possible. This process is achieved with the minimal number of exchanged messages and while

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Section: Global Ms Dynamicmentioning

confidence: 99%

Meetings scheduling solver enhancement with local consistency reinforcement

Hassine

Ito

2006

Appl Intell

Self Cite

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“…In the Synchronous Interactions category, we identified five major Conversational Agent for IM AINI [39] Meeting Scheduling [22] [ 59,60] RESCH [62] MSRAC [8] [89]…”

Section: Synchronous Interactionsmentioning

confidence: 99%

“…The system is more compatible with the needs of actual organizations because it can relax users' preferences while keeping the overall consistency. MSRAC is extensible and experiments demonstrate its efficiency in handling situations with tight constraints [8].…”

Section: Descriptions Of the Systemsmentioning

confidence: 99%

Agent and multi-agent applications to support distributed communities of practice: a short review

Sato

Azevedo

Barthès

2011

Auton Agent Multi-Agent Syst

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This paper concerns the relationship between agents or multi-agent systems and distributed communities of practice. It presents a review of a number of agent and multiagent applications with features that could contribute to supporting distributed communities of practice. The association is promising because of features like autonomy, pro-activity, flexibility or ability to integrate systems that characterize agents and multi-agent systems. Furthermore, such an association is a step towards building mixed communities of humans and artificial agents. To understand how agents and multi-agent systems could answer some of the needs of distributed communities of practice, we organize the analyzed applications into five different categories defined by considering the main activities of a community, namely: Individual Participation, Synchronous Interactions, Asynchronous Interactions, Publishing and Community Cultivation. Such a classification helps us identify the relevant features of the current technology and determine some that should be further developed, e.g. to support community coordination or gather information related to virtual communities. For each application we selected, we present its main approach and point out its potential interest.

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“…Personal assistant agents are an emerging application whose integration into businesses, office environments, universities and research organizations, as well as other spheres of human activity, promises to enhance productivity by performing routine or mundane tasks and expediting coordinated activities [1,5,10,13,18]. To effectively accomplish these tasks, agents must be endowed with information about their users, that would preferably be kept private.…”

Section: Introductionmentioning

confidence: 99%

Privacy Loss in Distributed Constraint Reasoning: A Quantitative Framework for Analysis and its Applications

Maheswaran

Pearce

Bowring

et al. 2006

Auton Agent Multi-Agent Syst

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It is critical that agents deployed in real-world settings, such as businesses, offices, universities and research laboratories, protect their individual users' privacy when interacting with other entities. Indeed, privacy is recognized as a key motivating factor in the design of several multiagent algorithms, such as in distributed constraint reasoning (including both algorithms for distributed constraint optimization (DCOP) and distributed constraint satisfaction (DisCSPs)), and researchers have begun to propose metrics for analysis of privacy loss in such multiagent algorithms. Unfortunately, a general quantitative framework to compare these existing metrics for privacy loss or to identify dimensions along which to construct new metrics is currently lacking. This paper presents three key contributions to address this shortcoming. First, the paper presents VPS (Valuations of Possible States), a general quantitative framework to express, analyze and compare existing metrics of privacy loss. Based on a state-space model, VPS is shown to capture various existing measures of privacy created for specific domains of DisCSPs. The utility of VPS is further illustrated through analysis of privacy loss in DCOP algorithms, when such algorithms are used by personal assistant agents to schedule meetings among users. In addition, VPS helps identify dimensions along which to classify and construct new privacy metrics and it also supports their quantitative comparison. Second, the article presents key inference rules that may be used in analysis of privacy loss in DCOP algorithms under different assumptions. Third, detailed experiments based on the VPS-driven analysis lead to the following key results: (i) decentralization by itself does not provide superior protection of privacy in DisCSP/DCOP algorithms when compared with centralization; instead, privacy protection also requires the presence of uncertainty about agents' knowledge of the constraint graph. (ii) one needs to carefully examine the metrics chosen to measure privacy loss; the qualitative properties of privacy loss and hence the conclusions that can be drawn about an algorithm can vary widely based on the metric chosen. This paper should thus serve as a call to arms for further privacy research, particularly within the DisCSP/DCOP arena.

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An agent-based approach to solve dynamic meeting scheduling problems with preferences

Cited by 33 publications

References 14 publications

Meetings scheduling solver enhancement with local consistency reinforcement

Meetings scheduling solver enhancement with local consistency reinforcement

Agent and multi-agent applications to support distributed communities of practice: a short review

Privacy Loss in Distributed Constraint Reasoning: A Quantitative Framework for Analysis and its Applications

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