Arantza Aldea

Emotions in human and artificial intelligence

Intelligence and emotions differentiate humans from animals. Emotion is part of a persons behaviour and certain feelings can affect his/her performance, emotions can even prevent a person from producing an intelligent outcome. Therefore, when a computer aims to emulate human behaviour, not only should this computer think and reason, but it should also be able to show emotions. This paper presents a review of recent research that shows the importance of the emotions in human intelligence. This paper also presents the research that has been carried out into the incorporation of emotions to intelligent systems, how a computer can show affections and how to create intelligent agents that show emotions to other agents that communicate with them in the same environment.

The scope of application of multi-agent systems in the process industry: three case studies

Abstract It has been suggested that multi-agent systems (MAS) are specially adequate for the solution of problems with a dynamic, uncertain and distributed nature. Within industrial applications, there is a wide spectrum of problems with these characteristics, in particular those covering the modelling of artifacts, methodologies and organisations. Three case studies on the application of MAS in the process industry are presented. All of them relate to tools that are being developed to support very diverse core tasks in the process industry (and, by extension, the petroleum industry): • An intelligent search system composed of Internet information agents which are able to gather, compile and classify data available in web pages related to a specific technological domain. This search engine is the first step towards the construction of a knowledge management platform that will allow chemical process industries to improve their capabilities to monitor, predict and respond to technological trends and challenges. • A system to support the concurrent design of processes, to ease communication between engineers who perform design and keep them informed about the progress of the design process. • A tool to support the configuration of work teams. This tool will assist in the configuration of the most suitable team for a specific project. It takes into account the ideal size of the team (2 to n members); its specific composition (managers, engineers/scientists, assistants, etc.); and the proposed type of organisation (centralised, tree hierarchy, etc.). These case studies are representative of a large variety of the possible applications of agent based systems in the process industry.

A Multi-agent System for Organ Transplant Co-ordination

The co-ordination of human organ transplants is a difficult task that involves legal, clinical, organisational and human aspects within a complex distributed environment of hospitals and governmental institutions. We propose a Multi-Agent Architecture that is the kernel of an Intelligent Decision Support System to co-ordinate the Spanish activity in organ transplants.

Semantic-ART: a framework for semantic annotation of regulatory text

Converting regulatory texts to machine interpretable models can enhance the automation of compliance management (CM) processes. The process poses serious research challenges as the information to be extracted from the regulatory texts comes from different regulatory bodies and is in different formats. In this paper, we present the main problems that we have faced in this area and how we have tackled them. Our proposed framework, Semantic-ART, considers the use of semantic annotation (SA) techniques to extract the regulations automatically.

Towards semantic methodologies for automatic regulatory compliance support

Businesses and organizations must comply with requirements and expectations such as regulations, policies, mandates and guidelines to meet public standards and avoid hefty penalties. Checking compliance manually is a laborious, extensive and error-prone process. The problems in the process are, to some extent, alleviated by using computerized compliance management systems. However, these systems are experiencing challenges in coping with the frequent changes and updates in the regulations. This paper describes our research on the use of semantic web technologies to support compliance management. In particular, we propose a methodology, RegCMatic that supports the management of the compliance system. Its originality lies on automating the extraction of regulatory information from regulatory texts, and mapping regulations to organizational internal processes. Our proposed methodology is applied to the Pharmaceutical industry, where regulatory information is extracted from the Eudralex EU regulation and modeled using a semantic formalism.

A hierarchical approach for the redesign of chemical processes

An approach to improve the management of complexity during the redesign of technical processes is proposed. The approach consists of two abstract steps. In the first step, model-based reasoning is used to generate automatically alternative representations of an existing process at several levels of abstraction. In the second step, process alternatives are generated through the application of case-based reasoning. The key point of our framework is the modeling approach, which is an extension of the Multimodeling and Multilevel Flow Modeling methodologies. These, together with a systematic design methodology, are used to represent a process hierarchically, thus improving the identification of analogous equipment/sections from different processes. The hierarchical representation results in sets of equipment/sections organized according to their functions and intentions. A case-based reasoning system then retrieves from a library of cases similar equipment/sections to the one selected by the user. The final output is a set of equipment/sections ordered according to their similarity. Human intervention is necessary to adapt the most promising case within the original process.

Multi-agent systems for ontology-based information retrieval

Abstract The Web offers a huge amount of valuable information, but it is very hard and time consuming to retrieve thousands of web pages related to a concept, filter the relevant ones, analyse this information and integrate it in a knowledge repository. This paper describes one component of a knowledge management platform (h-TechSight project) that performs these tasks, the multi-agent search module (MASH). MASH employs a domain ontology to search for web pages that contain relevant information to each concept in the domain of interest. The search is then constrained to a specific domain to avoid as much as possible the analysis of irrelevant information.

Extracting meaningful entities from regulatory text: Towards automating regulatory compliance

Extracting essential meaning from the regulatory text helps in the automation of the Compliance Management (CM) process. CM is a process where organizations assure that the processes are run according to requirements and expectations. However, extraction of meaningful text from regulatory guidelines comes with many research challenges such as dealing with different document-format, implicit document-structure, textual ambiguity and complexity. In this paper, the extended version of the Semantic-ART framework is described, which focuses on tackling the challenges of document-structure identification and regulatory-entity extraction. An initial result has shown an inspirational result as compared to the previous version of the framework.

A systematic evaluation of mobile applications for diabetes management

This short paper contains a summary of work that is currently in progress towards the development of an intelligent, personalised tool for diabetes management. A preliminary part of the development process has consisted of a systematic evaluation of existing applications for mobile phones.

Simulation of work teams using a multi-agent system

When a complex project starts in industry the selection of team(s) is one of the first steps that must be done. The correct selection of people to integrate a team within a complex engineering project is not a trivial task. Team configuration is a type of business decision-making typically done by a manager based on his/her past experience and with the available information about the behaviour and interaction between the potential team members. In this work we propose a Multi-Agent System that provides information about the possible overall behaviour of a work team and present the first results obtained.