5639109
An improvement to matchmaking algorithms for middle agents
A question frequently asked in multi-agent systems (MASs) concerns the efficient search for suitable agents to solve a specific problem. To answer this question, different types of middle agents are usually employed. The performance of middle agents relies heavily on the matchmaking algorithms used. Matchmaking is the process of finding an appropriate provider for a requester through a middle agent. There has been substantial work on matchmaking in different kinds of middle agents. To our knowledge, almost all currently used matchmaking algorithms missed one point when doing matchmaking -- the matchmaking is only based on the advertised capabilities of provider agents. The actual performance of provider agents in accomplishing delegated tasks is not considered at all. This results in the inaccuracy of the matchmaking outcomes as well as the random selection of provider agents with the same advertised capabilities. The quality of service of different service provider agents varies from one agent to another even though they claimed they have the same capabilities. To this end, it is argued that the practical performance of service provider agents has a significant impact on the matchmaking outcomes of middle agents. An improvement to matchmaking algorithms is proposed, which makes the algorithms have the ability to consider the track records of agents in accomplishing delegated tasks. How to represent, accumulate, and use track records as well as how to give initial values for track records in the algorithm are discussed. A prototype is also built to verify the algorithm. Based on the improved algorithm, the matchmaking outcomes are more accurate and reasonable.
6709890
An agent-based hybrid framework for database mining
While knowledge discovery in databases (KDD) is defined as an iterative sequence of the following steps: data pre-processing, data mining, and post data mining, a significant amount of research in data mining has been done, resulting in a variety of algorithms and techniques for each step. However, a single data-mining technique has not been proven appropriate for every domain and data set. Instead, several techniques may need to be integrated into hybrid systems and used cooperatively during a particular data-mining operation. That is, hybrid solutions are crucial for the success of data mining. This paper presents a hybrid framework for identifying patterns from databases or multi-databases. The framework integrates these techniques for mining tasks from an agent point of view. Based on the experiments conducted, putting different KDD techniques together into the agent-based architecture enables them to be used cooperatively when needed. The proposed framework provides a highly flexible and robust data-mining platform and the resulting systems demonstrate emergent behaviors although it does not improve the performance of individual KDD techniques.
206618709
Building an Ontology for Financial Investment
Intelligent agent technologies hold great promise for the financial services and investment industries such as portfolio management. In financial investment, a multi-agent system approach is natural because of the multiplicity of information sources and the different expertise that must be brought to bear to produce a good recommendation (such as a stock buy or sell decision). The agents in a multi-agent system need to coordinate, cooperate or communicate with each other to solve a complex problem. However, ontologies are a key component in how different agents in a multi-agent system can communicate effectively, and how the knowledge of agents can develop. This paper presents a case study in building an ontology in financial investment. The lessons we learned from the construction process are discussed. Based on our ontology development experience and the current development of ontologies, a framework of next generation ontology construction tools, which is aimed to facilitate the ontology construction, is proposed.
45852164
An Agent-Based Hybrid Intelligent System for Financial Investment Planning
Many complex problems including financial investment planning require hybrid intelligent systems that integrate many intelligent techniques including expert systems, fuzzy logic, neural networks, and genetic algorithms. however, hybrid intelligent systems are difficult to develop due to complicated interactions and technique incompatibilities. this paper describes a hybrid intelligent system for financial investment planning that was built from agent points of view. this system currently consists of 13 different agents. the experimental results show that all agents in the system can work cooperatively to provide reasonable investment advice. the system is very flexible and robust. the success of the system indicates that agent technologies can significantly facilitate the construction of hybrid intelligent systems.
16604369
Reusing legacy COBOL code with UML collaboration diagrams via a Wide Spectrum Language
Many legacy systems were developed in COBOL, which still play an important role in business. It is an unavoidable issue for organisations to maintain or replace these COBOL systems. In order to make a better use of these legacy COBOL systems, research on modelling and reusing COBOL code are significant. This paper presents an approach to modelling legacy COBOL code with UML collaboration diagrams via a Wide Spectrum Language (WSL). Firstly, legacy COBOL code is transferred into WSL, which is an intermediate language. Secondly, WSL representation is restructured to eliminate GOTO statements. Then an object concept model is created by operating WSL representation. Finally, the collaboration diagrams are constructed based on this object concept model. These collaboration diagrams express the dynamic behaviour of the system, using the structural class and relationship elements of the model, and facilitate engineers to understand and reuse legacy COBOL code.
14083998
Towards CST-enhanced summarization
In this paper, we propose to enhance the process of automatic extractive multi-document text summarization by taking into account cross-document structural relationships as posited in Cross-document Structure Theory (CST). An arbitrary multidocument extract can be CST-enhanced by replacing low-salience sentences with other sentences that increase the total number of CST relationships included in the summary. We show that CST-enhanced summaries outperform their unmodified counterparts using the relative utility evaluation metric. We also show that the effect of a CST relationship on an extract depends on its type.
5201312
Synchronization recovery of variable-length codes
The synchronization recovery property of variable-length (VL) codes has been extensively studied. In the paper, the mean error propagation length (MEPL) and the variance of error propagation length (VEPL), which are the secondary performance criteria of a VL code, are introduced to measure the synchronization recovery capability of a VL code. For the same probability distribution, there exist many different VL codes which have the same redundancy as the Huffman code but quite different MEPLs and VEPLs. To find one of the VL codes which has the minimum MEPL is a very difficult problem. We present two design algorithms for finding minimum-redundancy VL codes with short MEPL and VEPL. These two algorithms are simple and have the property that the codewords are assigned one by one. The efficiency of the algorithms are tested extensively by comparing the algorithms with known construction methods available in literature. Actually, VL codes obtained by the two algorithms outperform almost all codes available.
8228858
Coverage-aware proxy placement for dynamic content management over the Internet
In an effort to differentiate service quality, service providers have resorted to employing Content Distribution Networks (CDNs) over the Internet CDNs deploy geographically distributed proxy servers which manage content on behalf of the service provider's servers for better performance and enhanced availability. In this paper we explore the proxy placement problem for content distribution over the Internet. Its goal is to strategically place a number of proxies in the network to optimize certain criteria which improve performance of proxies. We motivate the various necessary factors and constraints that need to be taken into account for a good placement of proxies over the Internet which reflect real world scenario more accurately and which we claim hitherto has not been completely addressed. We introduce a novel concept of host coverage characterizing every Autonomous Systems (AS) and use this stable, coarse grained measure as a long-term estimate of the load being serviced by the proxy system. We then pose an optimal formulation of the proxy placement problem taking into consideration all the relevant factors. We propose a couple of proxy placement algorithms that solve the above problem and analyze their behavior. Finally we present the performance of those algorithms against the optimal solution and other schemes proposed in literature. We also study the stability of the proposed algorithms through a variety of experiments.
33893889
Supporting stored video: reducing rate variability and end-to-end resource requirements through optimal smoothing
Variable-bit-rate (VBR) compressed video can exhibit significant multiple-time-scale bit-rate variability. In this paper we consider the transmission of stored video from a server to a client across a network, and explore how the client buffer space can be used most effectively toward reducing the variability of the transmitted bit rate. Two basic results are presented. First, we show how to achieve the greatest possible reduction in rate variability when sending stored video to a client with given buffer size. We formally establish the optimality of our approach and illustrate its performance over a set of long MPEG-1 encoded video traces. Second, we evaluate the impact of optimal smoothing on the network resources needed for video transport, under two network service models: deterministic guaranteed service (Chang 1994; Wrege et al. 1996) and renegotiated constant-bit-rate (RCBR) service (Grossglauser et al. 1997). Under both models, the impact of optimal smoothing is dramatic.