In multi-agent systems, agents are inclined to form coalitions to improve individual performance and perform tasks more efficiently. However, the most existing researches assume that the desired outcome is a coalition...
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In multi-agent systems, agents are inclined to form coalitions to improve individual performance and perform tasks more efficiently. However, the most existing researches assume that the desired outcome is a coalition structure that consists of disjoint coalitions where every agent that has joined a coalition is no longer available to join other coalitions, which leads to waste of resources. In a number of practical scenarios an agent may have to be involved in executing more than one task simultaneously, and distributing its resources to several completely different coalitions. To tackle such problems, we propose the concurrent formation of overlapping coalitions and introduce a two-dimensional binary encoding to search the coalition space. We mainly focus on the revision algorithm for invalid encodings. Specifically, by using the proposed revision algorithm, an agent may join in several different coalitions at the same time without any resource conflict. Moreover, we prove by mathematical induction that the proposed algorithm will not discard any invalid encoding and can revise any invalid encoding into a valid one. Finally, a contrast experiment is illustrated to demonstrate the proposed algorithm. (C) 2010 Elsevier B. V. All rights reserved.
This paper proposes a decomposition based algo- rithm for revision problems in classical propositional logic. A set of decomposing rules are presented to analyze the satis- fiability of formulas. The satisfiability of...
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This paper proposes a decomposition based algo- rithm for revision problems in classical propositional logic. A set of decomposing rules are presented to analyze the satis- fiability of formulas. The satisfiability of a formula is equivalent to the satisfiability of a set of literal sets. A decomposing function is constructed to calculate all satisfiable literal sets of a given formula. When expressing the satisfiability of a formula, these literal sets are equivalent to all satisfied models of such formula. A revision algorithm based on this decomposing function is proposed, which can calculate maximal contractions of a given problem. In order to reduce the memory requirement, a filter function is introduced. The improved algorithm has a good performance in both time and space perspectives.
The mountains in northern Xinjiang of China were studied during the snowmelt season. Multi-source fusions of live data of the Chinese Land Data Assimilation System (CLDAS, 0.05 degrees x 0.05 degrees, hourly data) wer...
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The mountains in northern Xinjiang of China were studied during the snowmelt season. Multi-source fusions of live data of the Chinese Land Data Assimilation System (CLDAS, 0.05 degrees x 0.05 degrees, hourly data) were used as real data, and the Central Meteorological Observatory guidance forecast (SCMOC, 0.05 degrees x 0.05 degrees, forecasting the following 10 days in 3 h intervals) was used as forecast data, both of which were issued by the China Meteorological Administration. The dynamic linear regression and the average filter correction algorithms were selected to revise the original forecast products for SCMOC. Based on the conventional temperature forecast information, we designed four temperature-rise prediction algorithms for essential factors affecting snowmelt. The temperature-rise prediction algorithms included the daily maximum temperature algorithm, daily temperature-rise-range algorithm, snowmelt temperature algorithm, and daily snowmelt duration algorithm. Four temperature-rise prediction values were calculated for each prediction product. The root-mean-squared error algorithm and temperature prediction accuracy algorithm were used to compare and test each prediction algorithm value from the time sequence and spatial distribution. Comprehensive tests showed that the forecast product revised by the average filter algorithm was superior to the revised dynamic linear regression algorithm as well as the original forecast product. Through these algorithms, the more suitable temperature-rise forecast value for each grid point in the study area could be obtained at different prediction times. The comprehensive and accurate temperature forecast value in the mountainous snowmelt season could provide an accurate theoretical basis for the effective prediction of runoff in snowmelt areas and the prevention of snowmelt flooding.
Reputation Based Framework for Wireless Sensor Networks(RFSN) represent soft security mechanisms that complement traditional information security mechanisms. RFSN can prevent malicious of data from internal adversarie...
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Reputation Based Framework for Wireless Sensor Networks(RFSN) represent soft security mechanisms that complement traditional information security mechanisms. RFSN can prevent malicious of data from internal adversaries or faulty nodes. In this paper we add a new architecture called Trust-Holding-Agent (THA) to build a new Trust Framework model (RASN) improve on RFSN. The new framework model will be more suitable for wireless sensor networks. In addition, RASN is effective in resisting the On-Off Attack. The simulation results and analysis show that our scheme not only can fast detect the malicious nodes of On-off attacks, but also have incentive and punitive mechanism.
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