41297506
Evolutionary Negotiation in Agent-Mediated Commerce
Automated negotiation has become increasingly important since the advent of electronic commerce. In an efficient market, goods are not necessarily traded in a fixed price, and instead buyers and sellers negotiate among themselves to reach a deal that maximizes the payoffs of both parties. In this paper, a genetic agent-based model for bilateral, multi-issue negotiation is studied. The negotiation agent employs genetic algorithms and attempts to learn its opponent's preferences according to the history of the counter offers based upon the stochastic approximation. We also consider two types of agents: level- 0 agents are only concerned with their own interest while level-1 agents consider also their opponents' utility. Our goal is to develop an automated negotiator that guides the negotiation process so as to maximize both parties' payoff.
33842812
Anycast-Based Cooperative Proxy Caching
As one of the most popular applications currently running on the Internet, the World Wide Web is of an exponential growth in size, which results in the network congestion and server overloading. Web caching as an important technique aims at reducing network traffic, server load, and user-perceived retrieval delays by replicating popular contents on proxy caches. In our paper, we develop an anycast-based cooperative web proxy caching mechanism. It puts response time, hop counts, self-organized load balancing, adaption, and self-configuration as primary concerns. In our scheme, anycast is used to bring a server “nearest” to a client to improve overall performance, all proxies in a local network consists an anycast group. The object placement and replacement problems are formulated as an optimization problem and the solution is obtained by using an anycast-based cooperative proxy caching algorithm. Some simulation experiments have been conduced to evaluate the proposed scheme in terms of a wide range of performance metrics. Analytical and experimental results show that our algorithm outperforms some existing algorithms in response time, hop counts.
5692814
Mining associated implication networks: computational intermarket analysis
Current attempts to analyze international financial markets include the use of financial technical analysis and data mining techniques. In this paper, we propose a new approach that incorporates implication networks and association rules to form an associated network structure. The proposed approach explicitly addresses the issue of local vs. global influences between financial markets.
5220045
A study of the performance and parameter sensitivity of adaptive distributed caching
A self-organized approach to manage a distributed proxy system called Adaptive Distributed Caching (ADC) has been proposed previously [8]. We model each proxy as an autonomous agent that is equipped to decide how to deal with client requests using local information. Experimental results show that our ADC algorithm is able to compete with typical hashing-based approaches. This paper gives a full description of the self-organizing distributed algorithm, with a performance comparison based on hits and hops rate. Additional evaluation of the parameters caching-, multiple- and single-table size is also presented.
15907163
Characterizing Web usage regularities with information foraging agents
Researchers have recently discovered several interesting, self-organized regularities from the World Wide Web, ranging from the structure and growth of the Web to the access patterns in Web surfing. What remains to be a great challenge in Web log mining is how to explain user behavior underlying observed Web usage regularities. We address the issue of how to characterize the strong regularities in Web surfing in terms of user navigation strategies, and present an information foraging agent-based approach to describing user behavior. By experimenting with the agent-based decision models of Web surfing, we aim to explain how some Web design factors as well as user cognitive factors may affect the overall behavioral patterns in Web usage.
206446606
In search of the wisdom web
W eb intelligence offers a new direction for scientific research and development, pushing technology toward manipulating the meaning of data and creating a distributed intelligence that can actually get things done. WI explores the fundamental and practical impact that artificial intelligence and advanced information technology will have on the next generation of Web-empowered systems, services, and environments. In an era dominated by the World Wide Web, Grid computing, intelligent-agent technology, and ubiquitous social computing, WI represents information technology’s next challenge.
9354577
Identifying Faces in a 2D Line Drawing Representing a Manifold Object
A straightforward way to illustrate a 3D model is to use a line drawing. Faces in a 2D line drawing provide important information for reconstructing its 3D geometry. Manifold objects belong to a class of common solids and most solid systems are based on manifold geometry. In this paper, a new method is proposed for finding faces from single 2D line drawings representing manifolds. The face identification is formulated based on a property of manifolds: each edge of a manifold is shared exactly by two faces. The two main steps in our method are (1) searching for cycles from a line drawing and (2) searching for faces from the cycles. In order to speed up the face identification procedure, a number of properties, most of which relate to planar manifold geometry in line drawings, are presented to identify most of the cycles that are or are not real faces in a drawing, thus reducing the number of unknown cycles in the second searching. Schemes to deal with manifolds with curved faces and manifolds each represented by two or more disjoint graphs are also proposed. The experimental results show that our method can handle manifolds previous methods can handle, as well as those they cannot.
15518330
Enhanced Reputation Mechanism for Mobile Ad Hoc Networks
Interactions between entities unknown to each other are inevitable in the ambient intelligence vision of service access anytime, anywhere. Trust management through a reputation mechanism to facilitate such interactions is recognized as a vital part of mobile ad hoc networks, which features lack of infrastructure, autonomy, mobility and resource scarcity of composing light-weight terminals. However, the design of a reputation mechanism is faced by challenges of how to enforce reputation information sharing and honest recommendation elicitation. In this paper, we present a reputation model, which incorporates two essential dimensions, time and context, along with mechanisms supporting reputation formation, evolution and propagation. By introducing the notion of recommendation reputation, our reputation mechanism shows effectiveness in distinguishing truth-telling and lying agents, obtaining true reputation of an agent, and ensuring reliability against attacks of defame and collusion.
911649
Emergent Constraint Satisfaction Through Multi-Agent Coordinated Interaction
We present a methodology, called Constraint Partition and Coordinated Reaction (CP&CR), for distributed constraint satisfaction based on partitioning the set of constraints into subsets of different constraint types. Associated with each constraint type is a set of specialised agents, each of which is responsible for enforcing constraints of the specified type for the set of variables under its jurisdiction. Variable instantiation is the joint responsibility of a set of agents, each of which has a different perspective on the instantiation according to a particular constraint type and can revise the instantiation in response to violations of the specific constraint type. The final solution emerges through incremental local revisions of an initial, possibly inconsistent, instantiation of all variables. Solution revision is the result of coordinated local reaction of the specialised constraint agents. We have applied the methodology to job shop scheduling, an NP-complete constraint satisfaction problem. Utility of different types of coordination information in CP&CR was investigated. In addition, experimental results on a benchmark suite of problems show that CP&CR performed considerably well as compared to other centralised search scheduling techniques, in both computational cost and number of problems solved.
15792710
Markers improve clustering of CGH data
MOTIVATION
We consider the problem of clustering a population of Comparative Genomic Hybridization (CGH) data samples using similarity based clustering methods. A key requirement for clustering is to avoid using the noisy aberrations in the CGH samples.


RESULTS
We develop a dynamic programming algorithm to identify a small set of important genomic intervals called markers. The advantage of using these markers is that the potentially noisy genomic intervals are excluded during the clustering process. We also develop two clustering strategies using these markers. The first one, prototype-based approach, maximizes the support for the markers. The second one, similarity-based approach, develops a new similarity measure called RSim and refines clusters with the aim of maximizing the RSim measure between the samples in the same cluster. Our results demonstrate that the markers we found represent the aberration patterns of cancer types well and they improve the quality of clustering significantly.


AVAILABILITY
All software developed in this paper and all the datasets used are available from the authors upon request.
33401134
Distributed Group Management for Track Initiation and Maintenance in Target Localization Applications
The tradeoff between performance and scalability is a fundamental issue in distributed sensor networks. In this paper, we propose a novel scheme to efficiently organize and utilize network resources for target localization. Motivated by the essential role of geographic proximity in sensing, sensors are organized into geographically local collaborative groups. In a target tracking context, we present a dynamic group management method to initiate and maintain multiple tracks in a distributed manner. Collaborative groups are formed, each responsible for tracking a single target. The sensor nodes within a group coordinate their behavior using geographically-limited message passing. Mechanisms such as these for managing local collaborations are essential building blocks for scalable sensor network applications.