Environmental Decision Support: a Multi-Agent Approach

The environmental management domain is vast and encompasses many identifiable activities: impact assessment, planning, project evaluation, etc. In particular, this paper focusses on the modelling of the project evaluation activity. The environmental decision support system under development aims to provide assistance to project developers in the selection of adequate locations, guaranteeing the compliance with the applicable regulations and the existing development plans as well as satisfying the specified project requirements. The inherent multidisciplinarity features of this activity lead to the adoption of the Multi-Agent paradigm, and, in particular, to the modelling of the involved agencies as a community of cooperative autonomous agents, where each agency contributes with its share of problem solving to the final system’s recommendation. To achieve this behaviour the many conclusions of the individual agencies have to be justifiably accommodated: not only they may differ, but can be interdependent, complementary, irreconcilable, or simply, independent. We propose different solutions (involving both local and global consistency) to support the adequate merge of the distinct perspectives that inevitably arise during this type of decision making.

Environmental Decision Support: a Distributed Artificial Intelligence Approach

Decision making in any environmental domain is a complex and demanding activity, justifying the development of dedicated decision support systems. Every decision is confronted with a large variety and amount of constraints to satisfy as well as contradictory interests that must be sensibly accommodated. The first stage of a project evaluation is its submission to the relevant group of public (and private) agencies. The individual role of each agency is to verify, within its domain of competence, the fulfilment of the set of applicable regulations. The scope of the involved agencies is wide and ranges from evaluation abilities on the technical or economical domains to evaluation competences on the environmental or social areas. The second project evaluation stage involves the gathering of the recommendations of the individual agencies and their justified merge to produce the final conclusion. The incorporation and accommodation of the consulted agencies opinions is of extreme importance: opinions may not only differ, but can be interdependent, complementary, irreconcilable or, simply, independent. The definition of adequate methodologies to sensibly merge, whenever possible, the existing perspectives while preserving the overall legality of the system, will lead to the making of sound justified decisions. The proposed Environmental Decision Support System models the project evaluation activity and aims to assist developers in the selection of adequate locations for their projects, guaranteeing their compliance with the applicable regulations.

Tornar-se adulto na Casa 5: promover a autonomia individual em Apartamento de Autonomização

Na ausência de uma retaguarda familiar capaz de se constituir como uma rede de segurança e apoio ao desenvolvimento integral de adolescentes com medida de promoção e proteção, o Apartamento de Autonomização oferece um espaço no qual os jovens podem treinar competências que lhes assegurem um futuro autónomo e minimizem os riscos de exclusão social. Esta resposta social propõe-se preparar adolescentes, em transição para a adultez juvenil, para a conquista da responsabilidade de se autoprotegerem, de cuidarem de si próprios e de assumirem a sua identidade perante os outros. Todavia, um projeto de Autonomização de Vida revela-se um desafio, não apenas para os jovens, como também para as famílias e para os profissionais que com eles trabalham. Foram, precisamente, as dificuldades inerentes à Autonomização de Vida em contexto institucional que motivaram o desenvolvimento de um projeto em educação e intervenção social promotor da eficiência dessa resposta social em termos de promoção da autonomia e da transição bem-sucedida para a vida adulta. O presente relatório constitui, assim, um olhar retrospetivo sobre o Projeto “Tornar-se Adulto na Casa 5”, o qual, através da metodologia de Investigação-Ação Participativa, visou alcançar a finalidade proposta pelos participantes: “Promover uma autonomia plena dos jovens da Casa 5, com vista à transição bem-sucedida para a vida adulta após o término da medida de promoção e proteção”. Ainda que os resultados obtidos tenham sido moderadamente satisfatórios, o Projeto terá contribuído para o desenvolvimento de uma consciencialização mais crítica acerca das oportunidades e dos constrangimentos ao desenvolvimento da Autonomia, favorecendo, desejavelmente, a transição para vida adulta após a desinstitucionalização.

A Clinical Support System Based on Quality of Life Estimation

Quality of life is a concept influenced by social, economic, psychological, spiritual or medical state factors. More specifically, the perceived quality of an individual's daily life is an assessment of their well-being or lack of it. In this context, information technologies may help on the management of services for healthcare of chronic patients such as estimating the patient quality of life and helping the medical staff to take appropriate measures to increase each patient quality of life. This paper describes a Quality of Life estimation system developed using information technologies and the application of data mining algorithms to access the information of clinical data of patients with cancer from Otorhinolaryngology and Head and Neck services of an oncology institution. The system was evaluated with a sample composed of 3013 patients. The results achieved show that there are variables that may be significant predictors for the Quality of Life of the patient: years of smoking (p value 0.049) and size of the tumor (p value < 0.001). In order to assign the variables to the classification of the quality of life the best accuracy was obtained by applying the John Platt's sequential minimal optimization algorithm for training a support vector classifier. In conclusion data mining techniques allow having access to patients additional information helping the physicians to be able to know the quality of life and produce a well-informed clinical decision.