Agentes Inteligentes com Foco de Atenção Afetivo em Simulações Baseadas em Agentes

Simulations based on cognitively rich agents can become a very intensive computing task, especially when the simulated environment represents a complex system. This situation becomes worse when time constraints are present. This kind of simulations would benefit from a mechanism that improves the way agents perceive and react to changes in these types of environments. In other worlds, an approach to improve the efficiency (performance and accuracy) in the decision process of autonomous agents in a simulation would be useful. In complex environments, and full of variables, it is possible that not every information available to the agent is necessary for its decision-making process, depending indeed, on the task being performed. Then, the agent would need to filter the coming perceptions in the same as we do with our attentions focus. By using a focus of attention, only the information that really matters to the agent running context are perceived (cognitively processed), which can improve the decision making process. The architecture proposed herein presents a structure for cognitive agents divided into two parts: 1) the main part contains the reasoning / planning process, knowledge and affective state of the agent, and 2) a set of behaviors that are triggered by planning in order to achieve the agent s goals. Each of these behaviors has a runtime dynamically adjustable focus of attention, adjusted according to the variation of the agent s affective state. The focus of each behavior is divided into a qualitative focus, which is responsible for the quality of the perceived data, and a quantitative focus, which is responsible for the quantity of the perceived data. Thus, the behavior will be able to filter the information sent by the agent sensors, and build a list of perceived elements containing only the information necessary to the agent, according to the context of the behavior that is currently running. Based on the human attention focus, the agent is also dotted of a affective state. The agent s affective state is based on theories of human emotion, mood and personality. This model serves as a basis for the mechanism of continuous adjustment of the agent s attention focus, both the qualitative and the quantative focus. With this mechanism, the agent can adjust its focus of attention during the execution of the behavior, in order to become more efficient in the face of environmental changes. The proposed architecture can be used in a very flexibly way. The focus of attention can work in a fixed way (neither the qualitative focus nor the quantitaive focus one changes), as well as using different combinations for the qualitative and quantitative foci variation. The architecture was built on a platform for BDI agents, but its design allows it to be used in any other type of agents, since the implementation is made only in the perception level layer of the agent. In order to evaluate the contribution proposed in this work, an extensive series of experiments were conducted on an agent-based simulation over a fire-growing scenario. In the simulations, the agents using the architecture proposed in this work are compared with similar agents (with the same reasoning model), but able to process all the information sent by the environment. Intuitively, it is expected that the omniscient agent would be more efficient, since they can handle all the possible option before taking a decision. However, the experiments showed that attention-focus based agents can be as efficient as the omniscient ones, with the advantage of being able to solve the same problems in a significantly reduced time. Thus, the experiments indicate the efficiency of the proposed architecture

Estudo do potencial da técnica de nanossísmica para o monitoramento de hidrofraturamento em reservatórios de hidrocarbonetos

Hydraulic fracturing is an operation in which pressurised fluid is injected in the geological formation surrounding the producing well to create new permeable paths for hydrocarbons. The injection of such fluids in the reservoir induces seismic events. The measurement of this reservoir stimulation can be made by location these induced microseismic events. However, microseismic monitoring is an expensive operation because the acquisition and data interpretation system using in this monitoring rely on high signal-to-noise ratios (SNR). In general, the sensors are deployed in a monitoring well near the treated well and can make a microseismic monitoring quite an expensive operation. In this dissertation we propose the application of a new method for recording and location of microseismic events called nanoseismic monitoring (Joswig, 2006). In this new method, a continuous recording is performed and the interpreter can separate events from noise using sonograms. This new method also allows the location of seismic sources even when P and S phases onsets are not clear like in situations of 0 dB SNR. The clear technical advantage of this new method is also economically advantageous since the sensors can potentially be installed on the surface rather than in observation well. In this dissertation field tests with controlled sources were made. In the first test small explosives using fire works at 28 m (slant distances) were detected yealding magnitudes between -2.4 ≤ ML ≤ -1.6.. In a second test, we monitored perforation shots in a producing oil field. In this second test, one perforation shot was located with slant distances of 861 m and magnitude 2.4 ML. Data from the tests allow us to say that the method has potential to be used in the oil industry to monitor hydrofracture