Eurico Vasconcelos

A multi-agent simulator for teaching police allocation

This article describes the ExpertCop tutorial system, a simulator of the crime in an urban region. In ExpertCop, the students (police officers) configure and allocate an available police force according to a selected geographic region and then interact with the simulation. The student interprets the results with the help of an intelligent tutor, the Pedagogical Agent, observing how the crime behaves in the presence of the allocated preventive policing. The interaction between domain agents representing social entities as criminals and police teams drives the simulation. ExpertCop induces students to reflect on resource allocation. The pedagogical agent implents interaction strategies between the student and the geosimulator, designed to make simulated phenomena better understood. In particular, the agent uses a machine learning algorithm to identify patterns on simulation data and to formulate questions to the student about these patterns. Moreover, it explores the reasoning process of the domain agents by providing explanations that help the student to understand simulation events.

A Serious Game for Exploring and Training in Participatory Management of National Parks for Biodiversity Conservation: Design and Experience

In this paper, we discuss the experience in the design, use and evaluation of a serious game about participatory management of national parks for biodiversity conservation and social inclusion. Our objective is to help various stakeholders (e.g., environmentalist NGOs, communities, tourism operators, public agencies, and so on) to collectively understand conflict dynamics for natural resources management and to exercise negotiation management strategies for protected areas, one of the key issues linked to biodiversity conservation in national parks. Our serious game prototype combines, techniques such as: distributed role-playing games, support for negotiation between players, and insertion of various types of artificial agents (decision making agents, virtual players, assistant agents). After a general introduction to the project, we will present project’s current prototype architecture and results from game sessions, as well as some prospects for the future, namely: the design of assistant artificial agents and of virtual players and the integration of a viability-based simulation engine.

A conceptual framework for the design and evaluation of affective usability in educational geosimulation systems

In this article we propose a conceptual framework for associating the concepts of usability, computer education and affective quality. We analyze the interaction student-teacher under the light of learning strategies used in educational geosimulators for defining the main emotional constructs that are involved in this process. We elaborate this initial analysis by identifying which interactive objects should be associated with the identified emotional constructs. We associate these objects with an architecture that defines the basics components of an educational geosimulation system as well as the learning strategies used in this context. We illustrate the utility of the framework with an evaluation of an education geosimulator for police training as well as an evaluation of the students satisfaction during the interaction in different scenarios.

Using explanations of agents to increase understanding of simulations for tutoring police allocation

This article describes the ExpertCop tutorial system, a simulator of crime in an urban region. In ExpertCop, the students (police officers) configure and allocate an available police force according to a selected geographic region and then interact with the simulation. The student interprets the simulation results with the help of an intelligent tutor, the pedagogical agent, observing how crime behaves in the presence of the allocated preventive policing. The pedagogical agent implements a strategy of explanation of the agents individual behavior to make simulated phenomena better understood.