Edson Emílio Scalabrin

A Generic Model of Cognitive Agent to Develop Open Systems

The paper presents an approach to building multi-agent systems. We are interested in complex agents able to reason about their tasks, and to display a proactive behavior, when installed on a network of heterogeneous computers. We developed the concept of a generic agent (GAg), equipped with the basic communication and ”mental” structure, but ignorant, i.e., not containing any application expertise, nor having any knowledge about the external world. When building an application, actual agents are cloned from the generic agent. In addition, a specific environment, OSACA (Open System for Asynchronous Cognitive Agents), simplifies the process of creating agents on a network of heterogeneous machines. The paper discusses mainly the basic structure of the generic agent. Our approach is also illustrated with a small example of an agent which helps writing a technical paper in a research laboratory...

Trust and Reputation Models for Multiagent Systems

Finding reliable partners to interact with in open environments is a challenging task for software agents, and trust and reputation mechanisms are used to handle this issue. From this viewpoint, we can observe the growing body of research on this subject, which indicates that these mechanisms can be considered key elements to design multiagent systems (MASs). Based on that, this article presents an extensive but not exhaustive review about the most significant trust and reputation models published over the past two decades, and hundreds of models were analyzed using two perspectives. The first one is a combination of trust dimensions and principles proposed by some relevant authors in the field, and the models are discussed using an MAS perspective. The second one is the discussion of these dimensions taking into account some types of interaction found in MASs, such as coalition, argumentation, negotiation, and recommendation. By these analyses, we aim to find significant relations between trust dimensions and types of interaction so it would be possible to construct MASs using the most relevant dimensions according to the types of interaction, which may help developers in the design of MASs.

A learning agent to help drive vehicles

This paper presents the development of an intelligent agent used to assist vehicle drivers. The agent has a set of resources to generate its action policy: road and vehicle features and a knowledge base containing conduct rules. The perception of the agent is ensured by a set of sensors, which provide the agent with data such as speed, position and conditions of the brakes. The main agent behaviour is to carry out action plans involving: increase, maintain or reduce speed. The main effort of this research was the induction of conduct rules from data of previous trips. These rules form a classifier used for the selection of actions forming the conduction plan. Results observed with the experiments have showed that the proposed classifier increases the efficiency throughout the conduction of vehicles.

PANDORA: a multi-agent system using paraconsistent logic

This work is part of the Multicheck Project that defines architecture of cognitive and independents agents for the automatic treatment of handwritten Brazilian bank checks. The concept of autonomous agents allows us to organize the application knowledge and brings several own benefits to the approach. The choice of this approach is supported in a triple hypothesis. First, the nature of the problem in question allows decomposition in well-defined tasks, and each of them can be encapsulated in an independent agent. Second, the natural capability of interaction of the agents makes the check treatment process more robust, solving situations apparently difficult. Third, the natural parallelism between the agents can contribute to implement an application with high performance.

Objetos virtuais para apoio ao processo ensino-aprendizagem do exame físico em enfermagem

Objective: To describe the process of constructing virtual learning objects of physical examination in nursing. Methods: The study involved developing a product and research included four phases: planning, theoretical model development and evaluation of virtual objects by 19 experts and 38 students. Results: We stress the importance of steps to build virtual objects. In this overall assessment, for the average ranking of the 31 variables studied, 18 achieved scores between 4-5, 11 had scores between 3 3.9, and 2 had scores between 2 2.9. Conclusion: An innovation for consolidating the use of integrated computer technology into undergraduate nursing education must support the teaching and learning of physical examination in nursing, optimizing intra-and extracurricular activities and maximizing learningObjective: To describe the process of constructing virtual learning objects of physical examination in nursing. Methods: The study involved developing a product and research included four phases: planning, theoretical model development and evaluation of virtual objects by 19 experts and 38 students. Results: We stress the importance of steps to build virtual objects. In this overall assessment, for the average ranking of the 31 variables studied, 18 achieved scores between 4-5, 11 had scores between 3 - 3.9, and 2 had scores between 2 - 2.9. Conclusion: An innovation for consolidating the use of integrated computer technology into undergraduate nursing education must support the teaching and learning of physical examination in nursing, optimizing intra-and extracurricular activities and maximizing learning outcomes.

Lessons learned from a simulated environment for trains conduction

This paper consolidates and discuss the results of a software agent development, named SDriver, which is able to drive an intercity freight train in a secure, economic and fast way. The SDriver executes a small set of instructions, named: reducing, increasing or maintaining the acceleration point, and start breaking. Three approaches have been studied to implement the core of SDriver: (i) machine learning (classification methods), (ii) distributed constraint optimization, and (iii) specialized rules (if-then). The SDriver performance was evaluated comparing fuel consumption and actions similarity with a real conduction, using a simulated environment. The validation of the knowledge discovered from the machine learning approach was done quantitatively, calculating a degree of similarity between the simulation and the history of travel. The main results are expressed by their mean values: 32% of fuel consumption reduction and 85% action similarity between the SDriver and the real conductor.

Virtual objects to support the teaching-learning process of physical examination in nursing

Objective: To describe the process of constructing virtual learning objects of physical examination in nursing. Methods: The study involved developing a product and research included four phases: planning, theoretical model development and evaluation of virtual objects by 19 experts and 38 students. Results: We stress the importance of steps to build virtual objects. In this overall assessment, for the average ranking of the 31 variables studied, 18 achieved scores between 4-5, 11 had scores between 3 3.9, and 2 had scores between 2 2.9. Conclusion: An innovation for consolidating the use of integrated computer technology into undergraduate nursing education must support the teaching and learning of physical examination in nursing, optimizing intra-and extracurricular activities and maximizing learningObjective: To describe the process of constructing virtual learning objects of physical examination in nursing. Methods: The study involved developing a product and research included four phases: planning, theoretical model development and evaluation of virtual objects by 19 experts and 38 students. Results: We stress the importance of steps to build virtual objects. In this overall assessment, for the average ranking of the 31 variables studied, 18 achieved scores between 4-5, 11 had scores between 3 - 3.9, and 2 had scores between 2 - 2.9. Conclusion: An innovation for consolidating the use of integrated computer technology into undergraduate nursing education must support the teaching and learning of physical examination in nursing, optimizing intra-and extracurricular activities and maximizing learning outcomes.

An architecture of BDI agent for autonomous locomotives controller

In this paper we propose an architecture of intelligent agent for automatic locomotives operating. The system agent generates its action policy using a set of resources, such as type of railway, composition, belief perception and reasoning about the actions. The focus of the operator agent is directed to the choice of acceleration points (gear) and preparation of travel plans in a journey guided by goals and objectives. The system is equipped with a module capable to plan the actions to move the vehicle from an initial point P to an end point Q and an executor module that implements the generated plan and modifies the state of the environment. For this purpose, we use the mental model that is based on the triple Belief, Desire and Intention (BDI) to which the perception of the agent is guaranteed by a set of sensors that provide speed information, position and breaks condition. The main focus on this research is the usage of mental model BDI for the resolution of a problem that combines travel naturally conflicting factors, such as safety, time and fuel consumption. Experimental results show that the developed architecture using the mental model BDI increases the efficiency of autonomous vehicles operating.

Using asymmetric keys in a certified trust model for multiagent systems

We present a contribution based on encryption to the model for the certification of trust in multiagent systems. The originality of the proposal remains in the use of asymmetric keys that allow the local storage of testimonies with the service agents that were assessed. The aim is to raise the level of efficiency that client agents have when contracting specialized service agents. To reach this objective we make three hypotheses: (i) client agents are able to measure and inform the quality of a service they receive from a service agent; (ii) distributed certificate control is possible if every service agent stores the certificates it receives from its client agents and, (iii) the content of a certificate can be considered safe as long as the public and private keys used to encrypt the certificate remain safe. This approach reduces some weak points of trust models that rely on the direct interaction between service and client agents (direct trust) or those that rely on testimony obtained from client agents (propagated trust). Simulation showed that encrypted certificates of trust improved the efficiency of client agents when choosing their service provider agents. The reason seems to be that the reputation of a given service provider agent is based on the reputation it has among the totality of client agents that used its services.

An Empirical Study of Combined Classifiers for Knowledge Discovery on Medical Data Bases

This paper compares the accuracy of combined classifiers in medical data bases to the same knowledge discovery techniques applied to generic data bases. Specifically, we apply Bagging and Boosting methods for 16 medical and 16 generic data bases and compare the accuracy results with a more traditional approach (C4.5 algorithm). Bagging and Boosting methods are applied using different numbers of classifiers and the accuracy is computed using a cross-validation technique. This paper main contribution resides in recommend the most accurate method and possible parameterization for medical data bases and an initial identification of some characteristics that make medical data bases different from generic ones.