Resilient Team Formation with Stabilisability of Agent Networks for Task Allocation

Team formation (TF) faces the problem of defining teams of agents able to accomplish a set of tasks. Resilience on TF problems aims to provide robustness and adaptability to unforeseen events involving agent deletion. However, agents are unaware of the inherent social welfare in these teams. This article tackles the problem of how teams can minimise their effort in terms of organisation and communication considering these dynamics. Our main contribution is twofold: first, we introduce the Stabilisable Team Formation (STF) as a generalisation of current resilient TF model, where a team is stabilisable if it possesses and preserves its inter-agent organisation from a graph-based perspective. Second, our experiments show that stabilisability is able to reduce the exponential execution time in several units of magnitude with the most restrictive configurations, proving that communication effort in subsequent task allocation problems are relaxed compared with current resilient teams. To do so, we developed SBB-ST, a branch-and-bound algorithm based on Distributed Constrained Optimisation Problems (DCOP) to compute teams. Results evidence that STF improves their predecessors, extends the resilience to subsequent task allocation problems represented as DCOP, and evidence how Stabilisability contributes to resilient TF problems by anticipating decisions for saving resources and minimising the effort on team organisation in dynamic scenarios.

Development of a Tool for Team Formation in Engineering Education

Efficient team formation presents challenges both for the industry and the academia, especially among first year students. In academia, the difficulty is due to a lack of familiarity between instructors and new students at the beginning of each semester while in the industry, the issue is the incomplete picture of new employee’s personality by the supervisors. The quality of the team greatly affects both the team member experience as well as the outcome of assigned projects. There is a strong need to create a tool or a program that allows instructors and supervisors to create effective teams with evenly distributed skills amongst the teams in a timely fashion. Studies show that the balance of skills, rather than the presence of highly skilled individuals, leads to successful teams. The ultimate goal is to create a tool that will give teams the opportunity to operate at their maximum potential. This paper focuses on the creation of teams for first year students of engineering. The outcome is based on the results of a project assigned to a team of second year engineering students. The choice of second year students was dictated by the need to have students who had already experienced the adverse effects of malfunctioning teams during their previous projects. The goal of the project was to design a software and user interface for a tool that instructors could use to create optimal project teams in an efficient manner.

A novel state space reduction algorithm for team formation in social networks

Team formation (TF) in social networks exploits graphs (i.e., vertices = experts and edges = skills) to represent a possible collaboration between the experts. These networks lead us towards building cost-effective research teams irrespective of the geolocation of the experts and the size of the dataset. Previously, large datasets were not closely inspected for the large-scale distributions & relationships among the researchers, resulting in the algorithms failing to scale well on the data. Therefore, this paper presents a novel TF algorithm for expert team formation called SSR-TF based on two metrics; communication cost and graph reduction, that will become a basis for future TF’s. In SSR-TF, communication cost finds the possibility of collaboration between researchers. The graph reduction scales the large data to only appropriate skills and the experts, resulting in real-time extraction of experts for collaboration. This approach is tested on five organic and benchmark datasets, i.e., UMP, DBLP, ACM, IMDB, and Bibsonomy. The SSR-TF algorithm is able to build cost-effective teams with the most appropriate experts–resulting in the formation of more communicative teams with high expertise levels.

A Chemistry-Oriented Cost-Effective Expert Team Formation in Social Networks

<p>The growth of social networks in modern information systems has enabled the collaboration of experts at an unprecedented scale. Given a social network and a task consisting of a set of required skills, Team Formation (TF) aims at finding a team of experts who can cover the required skills and can communicate in an effective manner. However, this definition has been interpreted as the problem of finding teams with minimum communication cost which neglects two aspect of team formation in real life. The first is that in reality experts are multi-skilled, hence communication cost cannot be a fixed value and should vary according to the channels employed. The second ignored aspect is disregarding teams with high expertise level who can still satisfy the required communication level. To tackle above mentioned issues, I introduce a dynamic formof communication for multi-facet relationships and use it to devise a novel approach called Chemistry Oriented Team Formation (ChemoTF) based on two new metrics; Chemistry Level and Expertise Level. Chemistry Level measures scale of communication required by the task andExpertise Level measures the overall expertise among potential teams filtered by Chemistry Level. Moreover, I adopt a personnel cost metric to filter costly teams. The experimental results on the corpus compiled for this purpose suggests that ChemoTF returns communicative and cost-effective teams with the highest expertise level compared to state-of-the-art algorithms. The corpus itself is a valuable output which contains comprehensive scholarly information in the field of computer science.</p>

A Chemistry-Oriented Cost-Effective Expert Team Formation in Social Networks

<p>The growth of social networks in modern information systems has enabled the collaboration of experts at an unprecedented scale. Given a social network and a task consisting of a set of required skills, Team Formation (TF) aims at finding a team of experts who can cover the required skills and can communicate in an effective manner. However, this definition has been interpreted as the problem of finding teams with minimum communication cost which neglects two aspect of team formation in real life. The first is that in reality experts are multi-skilled, hence communication cost cannot be a fixed value and should vary according to the channels employed. The second ignored aspect is disregarding teams with high expertise level who can still satisfy the required communication level. To tackle above mentioned issues, I introduce a dynamic formof communication for multi-facet relationships and use it to devise a novel approach called Chemistry Oriented Team Formation (ChemoTF) based on two new metrics; Chemistry Level and Expertise Level. Chemistry Level measures scale of communication required by the task andExpertise Level measures the overall expertise among potential teams filtered by Chemistry Level. Moreover, I adopt a personnel cost metric to filter costly teams. The experimental results on the corpus compiled for this purpose suggests that ChemoTF returns communicative and cost-effective teams with the highest expertise level compared to state-of-the-art algorithms. The corpus itself is a valuable output which contains comprehensive scholarly information in the field of computer science.</p>

Consideration of approaches to forming a team when preparing students to participate in competitive events

The competitiveness of a modern university graduate is determined by his professional knowledge and skills, personal qualities, as well as the ability to make decisions, plan and organize work, and fulfill his role in team activities. Formation of the student’s ability to fulfill his role in a team is a general requirement for the training of a specialist in any field. The process of preparing university students for competitive events has great potential for the development of teamwork competencies. The aim of the study was to consider the specifics of preparing students for competitive events in the aspect of the approach of uniting students into teams. The peculiarities of preparing students for competitive programming in case of role-based and interpersonal methods of team formation were considered. The study used methods of observation, interviewing and questioning. The results of the study showed that the rolebased approach is more conducive to the development of student independence, the ability to make decisions, be responsible for the consequences of decisions, while the interpersonal approach allows to create conditions for the formation of team members’ ability to respond flexibly to changing circumstances. Thus, we can conclude about the various didactic possibilities of using role-based and interpersonal approaches to team building, about the need to use different methods for determining the composition of team members to solve educational problems in the learning process.

Understanding Matchmakers’ Experiences, Principles and Practices of Assembling Innovation Teams

The team composition of a project team is an essential determinant of the success of innovation projects that aim to produce novel solution ideas. Team assembly is essentially complex and sensitive decision-making, yet little supported by information technology (IT). In order to design appropriate digital tools for team assembly, and team formation more broadly, we call for profoundly understanding the practices and principles of matchmakers who manually assemble teams in specific contexts. This paper reports interviews with 13 expert matchmakers who are regularly assembling multidisciplinary innovation teams in various organizational environments in Finland. Based on qualitative analysis of their experiences, we provide insights into their established practices and principles in team assembly. We conceptualize and describe common tactical approaches on different typical levels of team assembly, including arranging approaches like “key-skills-first”, “generalist-first” and “topic-interest-first”, and balancing approaches like “equally-skilled-teams” and “high-expertise-teams”. The reported empirical insights can help to design IT systems that support team assembly according to different tactics.