12th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2007, Salamanca, Spain, November 12-16, 2007. Selected Papers

This book constitutes the refereed proceedings of the 12th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2007, held in Salamanca, Spain, in November 2007, in conjunction with the 7th Workshop on Artificial Intelligence Technology Transfer, TTIA 2007. The 28 revised full papers presented were carefully selected during two rounds of reviewing and improvement from 134 submissions. The papers address all current issues of artificial intelligence ranging from methodological and foundational aspects to advanced applications in various fields

Smart Buildings

This talk presents an efficient cyberphysical platform for the smart management of smart buildings http://www.deepint.net. It is efficient because it facilitates the implementation of data acquisition and data management methods, as well as data representation and dashboard configuration. The platform allows for the use of any type of data source, ranging from the measurements of a multi-functional IoT sensing devices to relational and non-relational databases. It is also smart because it incorporates a complete artificial intelligence suit for data analysis; it includes techniques for data classification, clustering, forecasting, optimization, visualization, etc. It is also compatible with the edge computing concept, allowing for the distribution of intelligence and the use of intelligent sensors. The concept of smart building is evolving and adapting to new applications; the trend to create intelligent neighbourhoods, districts or territories is becoming increasingly popular, as opposed to the previous approach of managing an entire megacity. In this paper, the platform is presented, and its architecture and functionalities are described. Moreover, its operation has been validated in a case study at Salamanca - Ecocasa. This platform could enable smart building to develop adapted knowledge management systems, adapt them to new requirements and to use multiple types of data, and execute efficient computational and artificial intelligence algorithms. The platform optimizes the decisions taken by human experts through explainable artificial intelligence models that obtain data from IoT sensors, databases, the Internet, etc. The global intelligence of the platform could potentially coordinate its decision-making processes with intelligent nodes installed in the edge, which would use the most advanced data processing techniques

Smart territories

The concept of smart cities is relatively new in research. Thanks to the colossal advances in Artificial Intelligence that took place over the last decade we are able to do all that that we once thought impossible; we build cities driven by information and technologies. In this keynote, we are going to look at the success stories of smart city-related projects and analyse the factors that led them to success. The development of interactive, reliable and secure systems, both connectionist and symbolic, is often a time-consuming process in which numerous experts are involved. However, intuitive and automated tools like “Deep Intelligence” developed by DCSc and BISITE, facilitate this process. Furthermore, in this talk we will analyse the importance of complementary technologies such as IoT and Blockchain in the development of intelligent systems, as well as the use of edge platforms or fog computing

Self-organizing multi-agent system for management and planning surveillance routes

This paper presents the THOMAS architecture, specially designed to model open multi-agent systems, and its application in the development of a multi-agent system for managing and planning surveillance routes for security personnel. THOMAS uses agents with reasoning and planning capabilities. These agents can perform a dynamic self-organization when they detect changes in the environment. THOMAS is appropriate for developing systems in highly dynamic environments similar to the one presented in this study, as demonstrated by the results obtained after having applied the system to a case study.Web of Science3151100108

Descubrimiento automático de mappings

Dentro de la problemática de la integración de información, los elementos claves son los mappings, unidades que relacionan las diferentes representaciones (ontologías, bases de datos, redes semánticas, etc. ). Y dentro de toda la colección de operaciones que los mappings llevan asociadas en todo su ciclo de vida, el cuello de botella se encuentra en su descubrimiento. Con este trabajo doctoral se pretende dar un paso más en este campo realizando un nuevo modelo de mappings lo menos limitado, y a la vez funcional, posible a diferentes representaciones y lo más versátil para la combinación de técnicas de descubrimiento, de toda índole, ya existentes y de nuevo cuño de manera automática, basándose en un sistema experto previamente construido a costa de evaluaciones sobre casos de uso reales

Self-Organizing Multi-Agent System for Management and Planning Surveillance Routes

This paper presents the THOMAS architecture, specially designed to model open multi-agent systems, and its application in the development of a multi-agent system for managing and planning surveillance routes for security personnel. THOMAS uses agents with reasoning and planning capabilities. These agents can perform a dynamic self-organization when they detect changes in the environment. THOMAS is appropriate for developing systems in highly dynamic environments similar to the one presented in this study, as demonstrated by the results obtained after having applied the system to a case study

Neural Systems in Distributed Computing and Artificial Intelligence

This Neurocomputing special issue presents the post-proceedings of the International Conference on Practical Applications on Agents and Multi-Agent Systems (PAAMS 2015) held in Salamanca in June 3th–5th, 2015. PAAMS provides an international forum to present and discuss the latest scientific developments and their effective applications, to assess the impact of the approach, and to facilitate technology transfer. PAAMS started as a local initiative, but has since grown to become the international yearly platform to present, to discuss, and to disseminate the latest developments and the most important outcomes related to real-world applications. It provides a unique opportunity to bring multi-disciplinary experts, academics and practitioners together to exchange their experience in the development and deployment of Agents and Multi-Agent Systems. PAAMS intends to bring together researchers and developers from industry and the academic world to report on the latest scientific and technical advances on the application of multi-agent systems, to discuss and debate the major issues, and to showcase the latest systems using agent based technology. It will promote a forum for discussion on how agent-based techniques, methods, and tools help system designers to accomplish the mapping between available agent technology and application needs. Other stakeholders should be rewarded with a better understanding of the potential and challenges of the agent-oriented approach

Proximity Detection Prototype Adapted to a Work Environment

This article presents a proximity detection prototype that uses ZigBee technology. The prototype is primarily oriented to proximity detection within an office environment and some of the particular characteristics specific to such an environment, including the integration of people with disabilities into the workplace. This allows the system to define and manage the different profiles of people with disabilities, facilitating their job assimilation by automatically switching on or off the computer upon detecting the user’s presence, or initiating a procedure that automatically adapts the computer to the personal needs of the user

An execution time neural-CBR guidance assistant

This paper presents a novel Ambient Intelligence based solution for shopping assistance. The core of the proposal is a CBR system developed for guiding and advising users in shopping areas. The CBR incorporates a neural based planner that identifies the most adequate plan for a given user based on user profile and interests. The RTPW neural network is based on the Kohonen one, and incorporates an interesting modification that allows a solution or a plan to be reached much more rapidly. Furthermore, once an initial plan has been reached, it is possible to identify alternatives by taking restrictions into account. The CBR system has been embedded within a deliberative agent and interacts with interface and commercial agents, which facilitate the construction of intelligent environments. This hybrid application, which works on execution time, has been tested and the results of the investigation and its evaluation in a shopping mall are presented within this paper

Combining case-based reasoning systems and support vector regression to evaluate the atmosphere–ocean interaction

This work presents a system for automatically evaluating the interaction that exists between the atmosphere and the ocean’s surface. Monitoring and evaluating the ocean’s carbon exchange process is a function that requires working with a great amount of data: satellite images and in situ vessel’s data. The system presented in this study focuses on computational intelligence. The study presents an intelligent system based on the use of case-based reasoning (CBR) systems and offers a distributed model for such an interaction. Moreover, the system takes into account the fact that the working environment is dynamic and therefore it requires autonomous models that evolve over time. In order to resolve this problem, an intelligent environment has been developed, based on the use of CBR systems, which are capable of handling several goals, by constructing plans from the data obtained through satellite images and research vessels, acquiring knowledge and adapting to environmental changes. The artificial intelligence system has been successfully tested in the North Atlantic Ocean, and the results obtained will be presented in this study