The trans-border region of Tijuana-San Diego with its multi-ethnic, multi-cultural society experiences a broad spectrum of social problems. The use of multi-agent systems to simulate such societies has increasingly been used as social research tool in these contexts, but is constrained by a lack of well defined contextual models. This paper proposes the use of the Viable Systems Model to underpin theory in multi-agent systems research and explores the benefits of using cybernetic thinking to understanding the problems being experienced in the Tijuana-San Diego conurbation.
Problems relating to team formation is common across many industrial sectors, including education, sport and general business. For Team Leaders, team member selection can be a critical challenge due to the complexity in creating a wellbalanced productive unit. It is beyond manual implementation to build near optimal teams as pools of employees grow. An essential requirement is teamwork skill, especially in engineering workgroups where the project member is expected to know how to collaborate with peers. In this paper, we use a social network analysis approach to represent social links between prospective team members and use the Belbin Team Roles as the main characteristic of prospective members. In our case study, based on an undergraduate computer engineering course, students expressed their preferences for working with three peers at the beginning of the course for an assessment. This information was used to distinguish groups within the social network using network analysis algorithms. We compared the network analysis results versus groups formed by a Teacher. Finally, we discuss the advantages and disadvantages of project teams, from a social network analysis approach, to making team formation recommendations into a socio-technical system.
The increasing use of mobile devices in indoor spaces brings challenges to location methods. This work presents a hybrid intelligent method based on data mining and Type-2 fuzzy logic to locate mobile devices in an indoor space by zones using Wi-Fi signals from selected access points (APs). This approach takes advantage of wireless local area networks (WLANs) over other types of architectures and implements the complete method in a mobile application using the developed tools. Besides, the proposed approach is validated by experimental data obtained from case studies and the cross-validation technique. For the purpose of generating the fuzzy rules that conform to the Takagi–Sugeno fuzzy system structure, a semi-supervised data mining technique called subtractive clustering is used. This algorithm finds centers of clusters from the radius map given by the collected signals from APs. Measurements of Wi-Fi signals can be noisy due to several factors mentioned in this work, so this method proposed the use of Type-2 fuzzy logic for modeling and dealing with such uncertain information.
Technology has become a necessity in our everyday lives and essential for completing activities we typically take for granted; technologies can assist us by completing set tasks or achieving desired goals with optimal affect and in the most efficient way, thereby improving our interactive experiences. This paper presents research that explores the representation of user interaction levels using an intelligent hybrid system approach with agents. We evaluate interaction levels of Human-Computer Interaction (HCI) with the aim of enhancing user experiences. We consider the description of interaction levels using an intelligent hybrid system to provide a decision-making system to an agent that evaluates interaction levels when using interactive modules of a museum exhibition. The agents represent a high-level abstraction of the system, where communication takes place between the user, the exhibition and the environment. In this paper, we provide a means to measure the interaction levels and natural behaviour of users, based on museum user-exhibition interaction. We consider that, by analysing user interaction in a museum, we can help to design better ways to interact with exhibition modules according to the properties and behaviour of the users. An interaction-evaluator agent is proposed to achieve the most suitable representation of the interaction levels with the aim of improving user interactions to offer the most appropriate directions, services, content and information, thereby improving the quality of interaction experienced between the user-agent and exhibition-agent.
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