Artificial Intelligence

Technologies

• Big data
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Technologies
Big data refers to a process that is used when traditional data mining and handling techniques cannot uncover the insights and meaning of the underlying data. Data that is unstructured or time sensitive or simply very large cannot be processed by relational database engines. This type of data requires a different processing approach called big data, which uses massive parallelism on readily-available hardware
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• Case-based Reasoning (CBR)
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Technologies
The case-based reasoining (CBR) is a paradigm that is based on the idea that similar problems have similar solutions. It draws on past experiences to solve new problems. Thus, if in a past moment it decided to solve a problem using a certain solution and once the solution is applied it achieves a certain result. Then it seems logical that, if a new problem is presented with characteristics similar to that previously solved in the past, it resorts to the acquired experience to give a solution. The acting model of the CBR system is known for the life cycle of the CBR system.
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• Experts systems
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Technologies
An expert system is capable of storing the knowledge of an expert in a particular specialty and limited, and in turn to solve problems through logical deduction-induction. They capture the knowledge of an expert and try to imitate the process of reasoning when solving problems in a given domain.
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• Fuzzy systems
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Technologies
A mathematical technique for dealing with imprecise data and problems that have many solutions rather than one. Fuzzy logic works with ranges of values, solving problems in a way that more resembles human logic, and it's used for solving problems with expert systems and real-time systems that must react to an imperfect environment of highly variable, volatile or unpredictable conditions.
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• Hybrid systems
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Technologies
The hybrid systems are dynamical systems that involve the interaction of continuous (real valued) states and discrete (finite valued) states. Applications where these types of dynamics play a prominent role will be highlighted.
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• Information fusion
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Technologies
The information fusion defines processes of organizing, merging and linking disparate information elements (e.g., map features, images, text reports, video, etc.) to produce a consistent and understandable representation of an actual or hypothetical set of objects and/or events in space and time.
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• Intelligent Modelling
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Technologies
The Intelligent Modelling is a revolutionary new approach to process modeling and pattern recognition, which is applicable to virtually any automated process. It captures the behavior of a process by building empirical models based on historical data. Deviations are catalogued into signatures to form patterns that are used to identify problems.
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• Multi-Agents System
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Technologies
One of the most representative fields in the study and development of systems of BISITE, is research on agent technology. It is a fact that the use of agents and multiagent systems for application development in dynamic and flexible environments is growing. In general, agents are being used in a variety of applications because they offer substantial advantages, including the naturalness of the model to conceptualize different types of software. Similarly, multi-agent systems represent a new way of analyzing, designing and implementing complex software systems. A multiagent system consists of several different autonomous agents interacting to achieve the desired function. Each agent performs a series of tasks and communicates with other agents to exchange information or demand a service. Both the agents and multiagent systems research fields are currently in full development, which are increasingly spending more resources.
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• Pattern recognition
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Technologies
The pattern recognition is a branch of artificial intelligence concerned with the classification or description of observations. It aims to classify data (patterns) based on either a priori knowledge or on statistical information extracted from the patterns. The patterns to be classified are usually groups of measurements or observations, defining points in an appropriate multidimensional space.
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• Predictive algorithms
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Technologies
Predictive algorithms use an explicit process model to predict the behavior of the system response. For each time interval, the predictive algorithm determines a control sequence that optimizes future behavior.
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• Social simulation
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Technologies
The social simulation is a research field that applies computational methods to study issues in the social sciences. The issues explored include problems in psychology,[1] organizational behavior,[2] sociology, political science, economics, anthropology, geography, engineering,[2] archaeology and linguistics.
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• Virtual organizations
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Technologies
The line dedicated to research on agent technology is expanding, including virtual organizations of agents. The agents’ organizations that self-adjust to benefit from its current environment are more important. These organizations may appear in dynamic or emerging agents societies, such as those suggested by the domains grid, peer-to-peer networks or other environments in which agents group dynamically to provide composite services. Social factors in the organizations of multi-agent systems are also increasingly important to structure interactions in open and dynamic worlds.
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