Sara Rodríguez González

Adaptive Agent-Based Environment Model to Enable the Teacher to Create an Adaptive Class

Learning management systems are used as a support tool in the process of knowledge sharing. Teachers add the material related to the domain of knowledge and also elaborate pedagogical mediation activities for the students. This process, in general, results in a learning environment that presents the same content for all participants, not taking into account the differences that exist between each of them, both in performance and behavior in the environment. The purpose of this work is to show an adaptive, agent-based environment model to enable the teacher to use some tools to create an adaptive class. In this model, resources and activities are made available to the participants in an individualized and adaptive way according to a previous configuration made by the teacher on the learning environment. The system was developed using Moodle to be used as a test bed case study and a basic calculus course was created to perform a practical evaluation test of the proposed model with real students as participants.

Organizations of agents in information fusion environments

Information fusion in a context-aware system is understood as a process that assembles assessments of the environment based on its goals. Advantages of intelligent approaches such as Multi-Agent Systems (MAS) and the use of Wireless Sensor Networks (WSN) within the information fusion process are emerging, especially in context-aware scenarios. However, it has become critical to propose improved and efficient ways to handle the enormous quantity of data provided by these approaches. Agents are a suitable option because they can represent autonomous entities by modeling their capabilities, expertise and intentions. In this sense, virtual organizations of agents are an interesting option/possibility because they can provide the necessary capacity to handle open and heterogeneous systems such as those normally found in the information fusion process. This paper presents a new framework that defines a method for creating a virtual organization of software and hardware agents. This approach facilitates the inclusion of context-aware capabilities when developing intelligent and adaptable systems, where functionalities can communicate in a distributed and collaborative way. Several tests have been performed to evaluate this framework and preliminary results and conclusions are presented.

Multiagent systems and self-organizative virtual organizations, a step ahead in adaptive MAS

Organizations of agents based on Virtual Organizations needs to be supported by a coordinated effort that explicitly determines how the agents should be organized and carry out the actions and tasks assigned to them. The interactions of a multi-agent system cannot be only related to the agent and the communication skills, but also to the concepts of organizational engineering. Moreover, nowadays there is a clear trend towards using methods and tools that can help to develop and simulate virtual organizations by means of multiagent systems (MAS). Simulation is used for several purposes ranging from work flow to systems procedures representation. The contribution from agent based computing to the field of computer simulation mediated by ABS (Agent Based Simulation) is a new paradigm for the simulation of complex systems that require a high level of interaction between the entities of the system. The main goal of this work is a new global coordination model for an agent organization in a simulation context. The innovation of this work consists of the dynamic and adaptive planning capability to distribute tasks among the agent of the organization. The middleware used for simulation makes it possible to visualize the emergent agent behaviour and the entity agent.

MASPI: A Multi Agent System for Prediction in Industry 4.0 Environment

Prediction is the way to optimize the maintenance task by determining the correct moment to interview, repair or replace equipment which the most difficult decision for companies in Industry 4.0 environment. This research present MASPI. I is a multiagent system based on advantages of virtual organization. The goal of MASPI is to be a reference model for making predictions about data captured by sensors installed in equipment or industrial machines. The capability of MASPI is evaluated by applying it to SCANIA trucks dataset, using machine learnings algorithms to obtain the prediction and compare their accuracy.

Machine Learning Predictive Model for Industry 4.0

In an Industry 4.0 environment, the data generated by sensors networks requires machine learning and data analysis techniques. Thus, organizations face both new opportunities and challenges, one of them is predictive analysis using computer tools capable of detecting patterns in the analyzed data from the same rules that can be used to formulate predictions. The Heating, Ventilation and Air Conditioning Systems (HVAC) control in an important number of industries: indoor climate, air’s temperature, humidity and pressure, creating an optimal production environment. In accordance, a case study is presented, in it a HVAC dataset was used to test the performance of the equipment and observe whether it maintains temperatures in an optimal range. The aim of this paper is making use of machine learning algorithms for the design of predictive models in the Industry 4.0 environment, using the previously mentioned dataset.

Improvement in the distribution of services in multi-agent systems with SCODA

T he distribution of services on multi-agent systems allows it to reduce to the agents their computational load. The functionality of the system does not reside in the agents themselves, however it is ubiquitously distributed so that allows you to perform tasks in parallel avoiding an additional computational cost to the elements in the system. The distribution of services that offers SCODA (Distributed and Specialized Agent Communities) allows an intelligent management of these services provided by agents of the system and the parallel execution of threads that allow to respond to requests asynchronously, which implies an improvement in the performance of the system at both the computational level as the level of quality of service in the control of these services. The comparison carried out in the case of study that is presented in this paper demonstrates the existing improvement in the distribution of services on systems based on SCODA.