For the larger search space when learning clause in Inductive Logic Programming, we defined the clause template. Firstly, we learn the clause templates by Genetic Algorithm, and then convert it to the requisite clause...
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For the larger search space when learning clause in Inductive Logic Programming, we defined the clause template. Firstly, we learn the clause templates by Genetic Algorithm, and then convert it to the requisite clauses by combining tag matrix and information gain sampling. We designed the corresponding fitness function and genetic operators. Theoretical analysis and experiment comparison show that this algorithm can reduce the search space, improve the search efficiency and can learn recursion clause. It is an effective clause learning algorithm.
Constraint satisfaction problems (CSPs) is an important research branch in artificial intelligence. Recently, dynamic CSP is proposed as a powerful tool for solving many real-world problems on dynamic environments. As...
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Constraint satisfaction problems (CSPs) is an important research branch in artificial intelligence. Recently, dynamic CSP is proposed as a powerful tool for solving many real-world problems on dynamic environments. As a result, several algorithms to solve dynamic CSPs are presented. Among those algorithms, local change (LC) algorithm based on solution reuse strategy is a method for solving many kinds of dynamic CSPs and efficient for flexible planning. On the basis of LC algorithm which is widely used, the tabu search strategy is integrated and a mini-conflict repair based algorithm is proposed, which is called Tabu_LC. The improved algorithm considers all the conflict variables as a whole, and then solves the sub-problems with branch and bound algorithm to find the best neighbor assignment, which improves the efficiency markedly. Furthermore, the Tabu_LC algorithm is implemented in the framework of constraint solving system Ming-yue 1.0, and compared with the LC algorithm using large amount of random CSPs. The experiment indicates that the improved algorithm has overwhelmed the LC algorithm on both the efficiency and quality of solutions.
In an open multi-agent of dynamic network environment, different mobile agents hope to carry on the communication for the problem of a certain domain. There is a need to avoid appearance of logical exception phenomeno...
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In an open multi-agent of dynamic network environment, different mobile agents hope to carry on the communication for the problem of a certain domain. There is a need to avoid appearance of logical exception phenomenon, and the term in this domain must be made to obtain consistency. A layer ontology services communication model named LOSCM is proposed in this paper. LOSCM has two primary advantages. First, it fully takes into account the factors that affect the communication, and using ontology can be represented in agent's knowledge base. Second, provided ontology does not belong to the public data source or have public ontologies, according to the concept loss degree and the concept related degree, LOSCM establishes a layering algorithm, which is able to avoid logical exception handling policies, ensure the right understanding of communication entity concept, and resolve the consistency problem of concept translation. It is shown by experiments that LOSCM is superior to other methods, and can effectively improve the communication consistency of a mobile agent system under certain conditions.
On the basis of the many-valued logics tableau reasoning, an automated reasoning expansion method based on set sign is presented. This approach which treats set signs as truth values can be applied to some methods and...
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On the basis of the many-valued logics tableau reasoning, an automated reasoning expansion method based on set sign is presented. This approach which treats set signs as truth values can be applied to some methods and techniques of reasoning suited to classical logics, which make reasoning reform from the non-classical logics to the classical logics. Through rewriting set signs and expansion rules, it is very easy to spread to modal logics, intuitionistic logics and so on. The technology can also be further spread to infinite-valued logic and logic with fuzzy quantifiers (such as T-calculus and S-calculus and so on). The theorem proving system-TSetTAP is implemented by using SWI-PROLOG language in microcomputer. Using method of set signs in the system, rule programming can be generated by only increasing reasoning rules in rule base. System need not be repaired. So some strategies and approaches used in classical logics can easily apply to non-classical logic. 900 logic questions in TPTP are proved using the system. The result shows TSetTAP makes the tableau close early and improve greatly in time efficiency and space efficiency of reasoning.
In this paper, we describe a fast semi-automatic segmentation algorithm. A nodes aggregation method is proposed for improving the running time and a Graph-Cuts method is used to model the segmentation problem. The who...
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Sequential pattern mining is one of the most important fields in data mining. In this paper, we propose a novel algorithm FSPAN (Fast Sequential Pattern mining algorithm) to do the sequence mining. FSPAN can mine all ...
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Identification of Transcription Factor Binding Sites (TFBS) from the upstream region of genes remains a highly important and unsolved problem particularly in higher eukaryotic genomes. In this paper, we propose a nove...
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In this paper, we present an efficient method for detecting collisions between highly deformable objects, which is a combination of newly developed stochastic method and Particle Swarm Optimization (PSO) algorithm. Fi...
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In this paper, we investigate the deficiency of Goyal and Egenhofer's method for modeling cardinal directional relations between simple regions and provide the computational model based on the concept of mathemati...
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Community structure is an important property of network. Being able to identify communities can provide invaluable help in exploiting and understanding both social and non-social networks. Several algorithms have been...
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Community structure is an important property of network. Being able to identify communities can provide invaluable help in exploiting and understanding both social and non-social networks. Several algorithms have been developed up till now. However, all these algorithms can work well only with small or moderate networks with vertexes of order 104. Besides, all the existing algorithms are off-line and cannot work well with highly dynamic networks such as web, in which web pages are updated frequently. When an already clustered network is updated, the entire network including original and incremental parts has to be recalculated, even though only slight changes are involved. To address this problem, an incremental algorithm is proposed, which allows for mining community structure in large-scale and dynamic networks. Based on the community structure detected previously, the algorithm takes little time to reclassify the entire network including both the original and incremental parts. Furthermore, the algorithm is faster than most of the existing algorithms such as Girvan and Newman＇s algorithm and its improved versions. Also, the algorithm can help to visualize these community structures in network and provide a new approach to research on the evolving process of dynamic networks.
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