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In this work we present a learning method based in temporal differences for learning the market prices for a supply chain manager in the TAC-SCM game scenario. The agent has two learning methods based in temporal differences. In one hand he learns the short term tendency of the market to adjust its prices proportionally to the rise or drop. He also learns a value of probability to elevate the prices...
Recently several psychologists have begun the exploration and study of emotions to explain better their functioning. The obtained results give evidence that emotions have an important impact on thinking, judgment, reasoning, memory and decision making of human being. In this work we describe a new faculty called artificial emotional intelligence (AEI), and we propose a model based on emotional intelligence...
In the groupware applications one of the principal aims is to supply a common context, so the more information gets shared, the more easily common context can be achieved. However, the sharing of information in this type of applications leads to provide security mechanisms. Controlling the access to resources and activities is a key element in system security. In this paper, we focus in access control...
In this paper, we draw on the ideas of previous work done by Drbohlav and Chantler [5], where a theoretical study on the optimal lighting configuration for photometric stereo was developed. They demonstrated that the known n light source azimuth angles should be equally spaced over 360/n degrees and the n light source elevation angles should be constant. In this paper, our aim is to develop a method...
In this paper we present a new approach for the solution of Markov decision processes based on the use of an abstraction technique over the action space, which results in a set of abstract actions. Markovian processes have successfully solved many probabilistic problems such as: process control, decision analysis and economy. But for problems with continuous or high dimensionality domains, high computational...
Accuracy and interpretability are two important objectives in the design of Fuzzy Logic model. In many real-world applications, expert experiences usually have good interpretability, but their accuracy is not always the best. Applying expert experiences to Fuzzy Logic model can improve accuracy and preserve interpretability. In this study we propose an accessible tool that helps medical interpretation...
School timetabling is a hard task that educational centers have to perform regularly and which implies a large waste of time and human efforts. For such reason designing techniques for the automatic generation of timetables is still of interest. Even though many contributions exist, the characteristics of the problem vary depending on the school policies, the country (laws), and other particular variables...
An important issue regarding the design of support vector machines (SVMs) is considered in this article, namely, the fine tuning of parameters in SVMs. This problem is tackled by using a self-adaptive genetic algorithm (GA). The same GA is used for feature selection. We validate our results implementing some statistical tests based on single domain benchmark data sets, which are used for comparison...
Automatic summarization systems often make use of sentence extraction methods to select significant content in texts. This paper presents two-sentence extraction strategies. The first one is based on a semantic analysis using word senses built by means of a network of lexical co-occurrences. The second one uses a combination of semantic and syntactical analysis to extract a set of relevant sentences...
We deal with knowledge retrieval within the context of Virtual Learning Environment (VLE). A good VLE should deliver relevant learning materials to the learner at the most appropriate time to facilitate knowledge acquisition by Problem-Based Learning (PBL). In PBL, students should retrieve information about a problem by working in small groups with the guidance of a learning facilitator providing...
In this task, an approach for single document summaries based on local topic identification and word frequency is proposed. In recent years, there has been increased interest in automatic summarization. The physical features are often used and have been successfully applied to this field; it also has some disadvantages of non-redundancy, structure and coherence. Therefore, we introduced logical structure...
This paper suggests a method that breaks a long sentence into simple sentences using not only syntactical information but also a sense of a word. Unlike uniformed sentences, common sentences are often ambiguous and frequently omit particles thus they should be divided into simple sentences at semantic level. This study shows the method that analyzes the dependency structure between predicate and complement...
Problem decomposition and state abstractions applied in the hierarchical problem solving often requires manual construction of a hierarchy structure in advance. This work is to provide some automatic algorithms for dimension reduction in problem solving. We propose cascading decomposition algorithm based on the spectral analysis on a normalized graph Laplacian to decompose the problem into several...
With the increase in the number of Web services and the value they are taking, discovery of services that meet the criteria of users becomes a major challenge. Currently the discovery process lacks of well-defined semantics, therefore it is difficult to obtain the non explicit meaning of services, such as functionality. In order to provide an accurate solution to the problem described above, in this...
The goal of this research is to provide an alternative for business processes evaluation and tracking, based on the analysis of non-structured information generated by such processes within the organization areas. In this article we introduce a method to determine the occurrence probability of a business process within the enterprisepsilas text documents. The proposed method introduces the use of...
The correct attribution of codes to economical activities is of ultimate importance for fiscal and administrative purposes. In a joint effort involving federal, state and city business regulating offices, the unification and automation of this codification process is in progress. As the input information is in the form of free textual entries, techniques used in multi-class, multi-label text categorization...
In multi-objective evolutionary optimization it is desirable to obtain a set of solutions usually called the Pareto optimal set. In this paper, some preliminary results are presented to approximate a Pareto optimal set considering an evolutionary adjustment of the parameters of a normal distribution function. The univariable and multivariable normal distribution functions are considered. Four test...
We present a method to reduce noise on signals applying complex auto-associative neural networks. Experimental results using the sine, triangular and sawtooth signals are performed to validate our results. This method is based on the use of complex neural networks learning and is capable of eliminating or reducing noise on learned signals. First, a training set consisting of signal values without...
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