Um ambiente de ensino colaborativo baseado em agentes inteligentes

Existe atualmente uma demanda pela modelagem de sistemas para suportar e mediar o trabalho e o aprendizado colaborativo através de uma rede de computadores. Este trabalho apresenta um ambiente de ensino colaborativo baseado em agentes inteligentes para a Internet. É definida uma arquitetura multi-agente que adota a estrutura de um sistema de federação de agentes. A estrutura principal desta arquitetura é definida através de três classes de agentes: agentes de interface, agentes de informação e agentes consultivos. Cada um dos agentes utilizam técnicas diferentes para resolver problemas específicos e interpretar situações. As principais abordagens de raciocínio utilizadas são raciocínio baseado em casos (o enfoque utilizado é ensino baseado em casos) e regras de produção. O presente trabalho discute a utilização da plataforma descrita como a base para a construção de um modelo colaborativo de ensino. Torna-se importante ressaltar que os agentes cooperam entre si para fornecerem o suporte de colaboração entre os estudantes. O ambiente desenvolvido possui a forma de um navegador inteligente, que além de permitir o acesso á Internet, incorpora serviços para auxiliar o estudante no processo de aprendizagem.Eje: Agentes inteligentesRed de Universidades con Carreras en Informática (RedUNCI

Um ambiente de ensino colaborativo baseado em agentes inteligentes

Existe atualmente uma demanda pela modelagem de sistemas para suportar e mediar o trabalho e o aprendizado colaborativo através de uma rede de computadores. Este trabalho apresenta um ambiente de ensino colaborativo baseado em agentes inteligentes para a Internet. É definida uma arquitetura multi-agente que adota a estrutura de um sistema de federação de agentes. A estrutura principal desta arquitetura é definida através de três classes de agentes: agentes de interface, agentes de informação e agentes consultivos. Cada um dos agentes utilizam técnicas diferentes para resolver problemas específicos e interpretar situações. As principais abordagens de raciocínio utilizadas são raciocínio baseado em casos (o enfoque utilizado é ensino baseado em casos) e regras de produção. O presente trabalho discute a utilização da plataforma descrita como a base para a construção de um modelo colaborativo de ensino. Torna-se importante ressaltar que os agentes cooperam entre si para fornecerem o suporte de colaboração entre os estudantes. O ambiente desenvolvido possui a forma de um navegador inteligente, que além de permitir o acesso á Internet, incorpora serviços para auxiliar o estudante no processo de aprendizagem.Eje: Agentes inteligentesRed de Universidades con Carreras en Informática (RedUNCI

Representing medical decision making strategies in a CBR system

Paper presented at the Sixth German Workshop on Case-Based Reasoning: Foundations, Systems, and Applications, Rostock, Germany.This paper describes and compares the development of two organizational structures to represent medical decision making strategies. We generate the solution to a new problem by applying a previous solution from a medical record in a CBR system that performs decision-making about hypertension drug therapy. The case libraries are structured in accordance with the approaches of flat memory and discrimination network. Cases are originated by a retrospective knowledge acquisition about 47 patients who underwent ambulatory care of a university hospital. The similarity-based retrieval employed in the flat structure resembles what physicians do when handling their routine cases of arterial hypertension. Physicians identify a similar case in memory by recognizing the content embedded in the new situation, like a script. The hypothetico-deductive method for searching the case solution follows a similar strategy to the one represented in the prioritized discrimination network. The inclusion of cases in the case library of the discrimination network required more complex procedures than in the case library of the flat memory. These two decision support systems could contribute significantly to patient care. The system we are researching on has educational purposes as well

Supporting working capital decisions through fuzzy analysis

Paper presented at the First International Conference of Industrial Engineering (ENEGEP/95), Sao Carlos, Brazil.Working Capital Management is concerned with the short term decisions regarding current assets and current liabilities. Although being related with the short term, the decisions must take into account the overall strategy of the firm and how effectively they are implemented at the operational level. The satisfaction of the goals and the measurement of the risks associated with these decisions are subjective and changeable depending on the situation. In this paper we propose the use of the Fuzzy Scenario Analysis to support the decisions at the operational level of a firm modeling the subjectivity of the process. The module we chose to illustrate the approach is related to purchase decisions. The method consists of modeling the satisfaction of an strategic goal (inventory conversion period) and the risk associated (of estimating sales) using fuzzy sets. We present an example where once these fuzzy sets are defined, the system suggests purchase decisions meeting the firm’s constraints regarding the amount of purchase and the associated benefits

Object oriented analysis and programming for a working capital management system

Paper presented at the IEEE/IAFE 1995 computational intelligence for financial engineering, CIFEr, New York, NY.The main purpose of this paper is to present an Object Oriented Analysis (OOA) of a firm and its accounting and financial environments for the implementation of a working capital management system. The object oriented analysis has been designed so that it can be used by different types and sizes of companies, (e.g., industrial, commercial or service). This versatility is a consequence of an important feature of the object oriented paradigm: the reusability of code. This OOA includes firm’s regular operations as well as tools and reports used in the management of working capital such as cash flows and estimated balance sheets. In order to demonstrate the functionality of the OOA, we discuss parts of the analysis that we have implemented successfully in the C++ object oriented programming language

Designing nutritional programs with case-based reasoning

Sixth German Workshop on Case-Based Reasoning: Foundations, Systems, and Applications, Rostock, Germany.This paper describes a system aimed at prescribing nutritional programs using Case-Based Reasoning (CBR). A nutritional program is a balanced dietetic plan aimed at better health conditions of the individuals. The nutritional task refers to prescribing a nutritional program as a therapy for a given nutritional disorder, in accordance to the patient’s characteristics that act as constraints, functions and goals. The main reason to use a case-based reasoning system in designing nutritional programs lies in the nature of the nutritional expert task, which is carried out by reusing past experiences. Nutritional professionals usually express their knowledge with generalizations, even when pointing specific instances as examples. This has motivated us to model the starting case base with a prototypical memory. Our approach to perform the nutritional task in a casebased reasoning system can be viewed as a two-fold process. First, the characteristics, symptoms, goals and restrictions are used to classify the new patient in a group associated to a diagnostic category. Second, the hypothetical case corresponding to the category that classifies the new case provides the design that represents the solution to be adapted to solve the new case. The system we are describing contemplates the nutritional task from the collection of patient's characteristics performing the diagnosis task implicitly, and prescribing the nutritional program (meal plan) to treat the respective nutritional disorder

Designing nutritional programs with case-based reasoning

Sixth German Workshop on Case-Based Reasoning: Foundations, Systems, and Applications, Rostock, Germany.This paper describes a system aimed at prescribing nutritional programs using Case-Based Reasoning (CBR). A nutritional program is a balanced dietetic plan aimed at better health conditions of the individuals. The nutritional task refers to prescribing a nutritional program as a therapy for a given nutritional disorder, in accordance to the patient’s characteristics that act as constraints, functions and goals. The main reason to use a case-based reasoning system in designing nutritional programs lies in the nature of the nutritional expert task, which is carried out by reusing past experiences. Nutritional professionals usually express their knowledge with generalizations, even when pointing specific instances as examples. This has motivated us to model the starting case base with a prototypical memory. Our approach to perform the nutritional task in a casebased reasoning system can be viewed as a two-fold process. First, the characteristics, symptoms, goals and restrictions are used to classify the new patient in a group associated to a diagnostic category. Second, the hypothetical case corresponding to the category that classifies the new case provides the design that represents the solution to be adapted to solve the new case. The system we are describing contemplates the nutritional task from the collection of patient's characteristics performing the diagnosis task implicitly, and prescribing the nutritional program (meal plan) to treat the respective nutritional disorder

Reusing cases to the automatic index assignment from textual documents

Paper presented at the Sixth German Workshop on Case-Based Reasoning: Foundations, Systems, and Applications, Rostock, Germany.This paper describes one solution developed to convert textual documents into formlike representations of cases. The experiences described by cases are textual descriptions of legal decisions. Indexing vocabulary and assignment theory contributed in gathering expert knowledge to define attributes and values as well as the required elements to employ template mining. Most index values are automatically extracted by the use of template mining. The multi-purpose index Theme is automatically assigned by reusing cases through an elaboration process. Seed cases are used to indicate values if the new case is a partial match to one in the case base

Case-based reasoning approach to reuse of experiential knowledge in software measurement programs

Paper presented at the Sixth German Workshop on Case-Based Reasoning: Foundations, Systems, and Applications, Rostock, Germany.For the successful application of innovative software engineering technologies in industry, the technologies have to evolve incrementally based on continuous feedback from practice. Experiences about their practical application have to be systematically collected and stored in corporate memories and reused in future software projects. This promotes the sharing of experiences across individuals and projects, the formulation of best practices and facilitates the successful application of tailored technologies in practice. This paper presents a case-based reasoning approach for capturing and reusing experiential knowledge on software measurement programs in industry. A representation structure for experiential measurement knowledge is described in detail and knowledge retrieval and acquisition techniques are presented