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12 Liu Q., Lu X., Ren F., Kuroiwa Sh. 20 MACD indicator 15 10 5 charts texts 0 comprehension accuracy time interest remembrance usefulness Fig. 4. evaluation experiment form. Such systems could begin with inputting semantic representation, subjecting it to a number of consecutive transformations until a surface structure results. Within this paper, the ESF based KR system can do the accurate and convenient transformation between all kinds of knowledge objects. Because not only the ESF schema combines standard KR with templates, but also it tends to use syntactically structured ”templates” – function (here the function has more changes than the common template), and allows the gaps as function’s parameters to be filled recursively for realizing linguistic expression like standard KR system. Therefore, we name our KR system – function based KR system. Furthermore, we utilize the XML and XSTL techniques to describe the ESF schema in this paper. Because the XML and XSTL have become the main techniques of information formalizing on Web, they supply the common rules for developers to format all information under one standard. Therefore, this schema using XML and XSTL techniques can be realized on Web for information’s integration, distribution and transformation. References [1] V. Mittal, J. Moore, G. Carenini and S.F. Roth, Describing Complex Charts in Natural Language: A Caption Generation System Computational Linguistics (1998, 24(3), pp. 431-467). [2] M. Theune, E. Klabbers, J. Pijper, E. Krahmer and J. Odijk, From data to speech: a general approach, Natural Language Engineering (2001, 7(1), pp. 47-86). [3] Susan W. McRoy, S. Channarukul and Syed S. Ali, An augmented template-based approach to text realization, Natural Language Engineering (2003, 9(4), pp. 381- 420). [4] M. White, Reining in CCG Chart Realization, in Proceedings of the 3rd International Conference on Natural Language Generation (2004). [5] Mary E. Foster and M. White, Assessing the Impact of Adaptive Generation in the COMIC Multimodal Dialogue System. in Proceedings of the Workshop on Knowledge and Reasoning in Practical Dialogue Systems (2005).
The Description Logic of Tasks 1 Zhang Hui Li Sikun College of Computer Science, National University of Defense Technology, Changsha, China qd_zhanghui@163.com Abstract. The logic of tasks can be used in AI as an alternative logic of planning and action, its main appeal is that it is immune to the frame problem and the knowledge preconditions problem other plan logics confront. A drawback the present logic of tasks has is that it is nondecidable (semidecidable only). This paper extends the logic of tasks to enable the task description by adapting description structure into it. A formal system DTL, which is sound, complete and decidable, for agent abilities specification and accomplishablity of tasks judgment is proposed. 1 Introduction The semantic used in the logic of tasks can claim to be a formalization of the resource philosophy associated with linear logic[4,5,6], if resources are understood as agents carrying out tasks. The formalism may also have a potential to be used in AI as an alternative logic of planning and action and its main appeal is that it is immune to the frame problem and the knowledge preconditions problem other plan logics confront [2,10]. A drawback the present logic of tasks has is that it is nondecidable (semidecidable only). Motivated by the success of description logic[7.8.9], in this paper we present a decidable logic system, the description logic of tasks that enable task description by adapting the description structure into the logic of tasks. In our paper the task may have parameter e.g. we can use C(x) denoting the task to clean x, x can be either room or lawn (room and lawn are constant). The expression α→β in our paper means that the accomplishment of task α is the condition to accomplish the task β, such as F(rake)→C(lawn) and F(mop)→C(room) express that the cleaner can clean the room if be given a mop and can clean the lawn if be given a rake respectively. A characteristic feature of description languages is their ability to represent other kinds of relationships, expressed by role, beyond IS-A relationships. The role has what is called a “value restriction,” denoted by the label ∀R. which expresses a limitation on the range of types of objects that can fill that role. In this paper we use role to express the relation between objects. For example R(room,mop) means that 1 Supported by the National Grand Fundamental Research 973 Program (2002CB312105) and 863 program (2004AA115130) of China. © A. Gelbukh, R. Monroy. (Eds.) Advances in Artificial Intelligence Theory Research on Computing Science 16, 2005, pp. 13-22
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subset. If so, the solution is not
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In some domains, one can use tricks
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Together, these three conditions en
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5 Evaluation PSIGRAPH was implement
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Multiagent Systems and Distributed
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This paper structure is as follows:
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0 1800 Decentralized execution Cent
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Compared to agent-enhanced approach
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100 A. Umre, I. Wakeman As well as
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102 A. Umre, I. Wakeman the request
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104 A. Umre, I. Wakeman 3.1 Results
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106 A. Umre, I. Wakeman 3.1.3 Slash
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108 A. Umre, I. Wakeman References
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Some Experiments on Corner Tracking
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Pattern Decomposition and Associati
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Object Classification Based on Asso
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Associative Processing Applied to W
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154 Castiello C., Fanelli A. of art
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168 J. Saade, A. Fakih The main rea
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170 J. Saade, A. Fakih possible or
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172 J. Saade, A. Fakih Although the
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Intelligent genetic algorithm: a to
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Intelligent Genetic Algorithm: A To
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Improved Ant Colony System using Su
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Building Block Filtering Genetic Al
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Evolutionary Training of SVM for Cl
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Natural Language Processing
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240 Hannon Ch. LEAP is developed us
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242 Hannon Ch. concepts immediately
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246 Hannon Ch. accessed. The concep
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248 Hannon Ch. a major factor. Init
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Characterization and Interpretation
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272 I. López, A. Rojano ing optima
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Editorial Board of the Volume Comit
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