Role and member selection in team formation using resource estimation for large-scale multi-agent systems

Hayano, Masashi; Hamada, D.; Sugawara, Toshiharu

doi:10.1016/j.neucom.2014.04.059

Cited by 20 publications

(4 citation statements)

References 21 publications

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“…Based on this idea, the authors propose applying a rigorous quantitative mathematical analysis for the selection process. Hayano et al (2014) propose the use of multi-agent systems in task-oriented situations with no prior knowledge of the resources or abilities of other agents. Another quantitative approach is proposed by Bredereck et al (2015) who mention a theoretical and mathematical approach using as constraints an attribute matrix, the cost to design each team, and team sizes.…”

Section: Literature Reviewmentioning

confidence: 99%

Decision Making Method to Select Team Members Applying Personnel Behavior Based Lean Model

Avilés-González¹,

Smith²,

Sawhney³

2016

Industrial Engineering and Management Systems

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Design of personnel teams has been studied from diverse perspectives; the most common are the people and systems requirements perspectives. All these point of view are linked, which is the reason why it is necessary to study them simultaneously. Considering this gap, a decision making model is developed based on factors, models, and requirements mentioned in the literature. The model is applied to a real case. The findings indicate that the Personnel Behavior Based Lean model (PBBL) can be converted into a decision making model for the selection of team members. The study is focused not only on the individual candidates' knowledge, skills, and aptitudes, but also on how the model considers the company requirements, conflicts, and the importance of each person to the project.

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Section: Literature Reviewmentioning

confidence: 99%

Decision Making Method to Select Team Members Applying Personnel Behavior Based Lean Model

Avilés-González¹,

Smith²,

Sawhney³

2016

Industrial Engineering and Management Systems

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“…Although it can allocate tasks/resources optimally in the sense of maximizing social welfare, it cannot be applied to dynamic environments where optimal solutions frequently vary. Team formation (or coalitional formation in a task-oriented model) is another approach in which individual agents identify the most appropriate member agent for each subtask on the basis of the learning of functionality and the capabilities of other agents (Coviello and Franceschetti, 2012;Hayano et al, 2014;Genin and Aknine, 2010;Abdallah and Lesser, 2004). However, this may cause conflicts in large-scale and busy MAS, as mentioned in Section 1.…”

Section: Related Workmentioning

confidence: 99%

“…However, this may cause conflicts in large-scale and busy MAS, as mentioned in Section 1. Our aim is to reduce such conflicts by building upon our previous work (Hayano et al, 2014) and introducing agents that switch from rational behavior to reciprocal behavior (and vise versa) on the basis of results of past collaboration.…”

Section: Related Workmentioning

confidence: 99%

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Switching Behavioral Strategies for Effective Team Formation by Autonomous Agent Organization

Hayano

Miyashita

Sugawara

2016

Proceedings of the 8th International Conference on Agents and Artificial Intelligence

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In this work, we propose agents that switch their behavioral strategy between rationality and reciprocity depending on their internal states to achieve efficient team formation. With the recent advances in computer science, mechanics, and electronics, there are an increasing number of applications with services/goals that are achieved by teams of different agents. To efficiently provide these services, the tasks to achieve a service must be allocated to agents that have the required capabilities and the agents must not be overloaded. Conventional distributed allocation methods often lead to conflicts in large and busy environments because high-capability agents are likely to be identified as the best team member by many agents, resulting in inefficiency of the entire system due to concentration of task allocation. Our proposed agents switch their strategies in accordance with their local evaluation to avoid conflicts occurring in busy environments. They also establish an organization in which a number of groups are autonomously generated in a bottom-up manner on the basis of dependability in order to avoid the conflict in advance while ignoring tasks allocated by undependable/unreliable agents. We experimentally evaluate our proposed method and analyze the structure of the organization that the agents established. 56

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A Solution for the Team Selection Problem Using ACO

Lugo

Bello

Nowé

et al. 2018

Lecture Notes in Computer Science

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Role and member selection in team formation using resource estimation for large-scale multi-agent systems

Cited by 20 publications

References 21 publications

Decision Making Method to Select Team Members Applying Personnel Behavior Based Lean Model

Decision Making Method to Select Team Members Applying Personnel Behavior Based Lean Model

Switching Behavioral Strategies for Effective Team Formation by Autonomous Agent Organization

A Solution for the Team Selection Problem Using ACO

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