Ana de Luis

Model for assigning roles automatically in egovernment virtual organizations

When working in conjunction with multiagent systems, virtual organizations attempt to simulate the functions and interactions of entities in different environments. Recent studies have addressed the problem of assigning roles to agents that form part of the organization, and incorporating new agents to carry out certain tasks. However, these studies are limited to defining the norms and rules that determine the behavior of the organization. The present study proposes a virtual organization model for egovernment environments to assign resources and minimize the required personnel by forecasting workloads. To this end, a neural network, queuing theory, and CBR are used to obtain an efficient distribution. Queuing theory can establish the number of agents with a specific role that are necessary to maximize profits, while the network distributes roles among agents according to their respective efficiency. The final part of the paper is focused on validating the plan developed inside a case study centered on e-government in order to obtain empirical results.

Hybrid Architecture for a Reasoning Planner Agent

This paper presents a hybrid architecture that facilitates the incur-poration of a case-based planning system as the reasoning motor for a deliberative agent. This architecture makes possible to solve a wide range of problems in terms of agents and multi-agent systems. The problems are resolved in terms of plans, using plans that have already been experienced.

Nature-inspired planner agent for health care

This paper presents an autonomous intelligent agent with a human thinking reasoning model, based on past experiences. The agent is developed to assist medical staff in geriatric residences. The health care process is a vital function, requiring nature-inspired solutions imitating the residence staff behaviours. An autonomous deliberative Case-Based Planner agent, AGALZ (Autonomous aGent for monitoring ALZheimer patients), is developed and integrated into an environment-aware multi-agent system, named ALZ-MAS (ALZheimer Multi-Agent System), to optimize health care in geriatric residences. ALZ-MAS is capable of obtaining information about the environment through RFID technology.

Healthcare information fusion using context-aware agents

Context aware systems have evolved into complex information systems capable of providing large quantities of information obtained from network sensors with heterogeneous characteristics This article proposes a multi-agent system that monitors patients and maintains a permanent fix on their location within a given context The system uses information provided by sensors distributed throughout the environment The system agents take the information they receive and fuse it to improve the decisions and actions involved in their processing The multi-agent system implements a SOA-based platform, which allows heterogeneous Wireless Sensor Networks to communicate in a distributed way This article presents the evaluation of the solutions provided by the agents through the information flow for the organization.

Cloud Computing in Bioinformatics

Cloud Computing presents a new approach to allow the development of dynamic, distributed and highly scalable software. For this purpose, Cloud Computing offers services, software and computing infrastructure independently through the network. To achieve a system that supports these characteristics, Service-Oriented Architectures (SOA) and agent frameworks exist which provide tools for developing distributed and multi-agent systems that can be used for the establishment of Cloud Computing environments. This paper presents a CISM@ (Cloud computing Integrated into Service-oriented Multi-Agent) architecture set on top of the platforms and frameworks by adding new layers for integrating a SOA and Cloud Computing approach and facilitating the distribution and management of functionalities. CISM@ has been applied to the real case study consisting of the analysis of microarray data and has allowed the efficient management of the allocation of resources to the different system agents.

Prediction System of Pollen Allergies in Mobile Devices

Although pollen allergies have a high incidence in society, it is not very common to use applications that provide data on pollen levels from different measuring points and also predict the allergies a user may experience. This paper introduces a system adapted to mobile devices that displays levels of pollen in the Spanish region of Castile and Leon in an easy way. The proposed system also processes the information provided by users about their health, and uses the historical data of pollen to detect and estimate allergies. The system incorporates an algorithm based on statistical tests to carry out the detection of allergies.

CAFCLA: A Conceptual Framework to Develop Collaborative Context-Aware Learning Activities

Advances appeared in Information and Communication Technologies along last years have given raise to new interaction ways between people and technology. Ambient Intelligences (AmI) is a multidisciplinary research area which promotes the use or technology in a transparent way to facilitate everyday tasks. Education is one field that benefits from AmI: collaboration between students in innovate ways, data acquisition from the context or real time location systems enhance learning processes. This paper presents CAFCLA, a framework aimed at designing, developing and deploying AmI-based educational scenarios where collaboration between students and contextual information are available every time and everywhere through multiple resources and communication protocols.

Dynamic model of distribution and organization of activities in multi-agent systems

Currently, the allocation of tasks is a problem in many different areas such as e-Goverment. Traditionally, the assignment is done manually; therefore it is necessary to anticipate workloads and employee characteristics. This article describes a system based on virtual organizations of agents that allows recommendations about planning of tasks to minimize the resources necessary for their accomplishment and to obtain the maximum profit. For this purpose, a hybrid artificial intelligence system with genetic algorithm, queuing theory and case-based reasoning is used to obtain an efficient distribution. The final part of the article is focused on validating the plan developed inside a case of study centered in the e-Government in order to obtain empirical results.

Context Aware Hybrid Agents on Automated Dynamic Environments

This paper presents an Ambient Intelligence based architecture model that uses intelligent hybrid agents with the ability to obtain automatic and real time information about the context using a set of technologies, such as radio frequency identification, wireless networks and wireless control devices, which can be implemented on a wide diversity of dynamic environments.

Dynamic Distribution of Tasks in Health-Care Scenarios

This paper presents a multiagent system that use an autonomous deliberative case-based reasoningagent to design an efficient working day. The system has been developed to plan and distribute tasks in a health care scenario, specifically in geriatric residences. This model generates a planning of tasks, minimizing the resources necessary for its accomplishment and obtaining the maximum benefits. For this purpose, the queuing theory and genetic algorithms have been include in a CBRarchitecture to obtain an efficient distribution. To evaluate the model, the obtained results have been compared with a previous method of planning based on neural networks.