38589580
A genetic agent-based negotiation system
Abstract Automated negotiation has become increasingly important since the advent of electronic commerce. Nowadays, goods are no longer necessarily traded at 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 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.
14178256
Distributed Problem Solving Without Communication - An Examination of Computationally Hard Satisfiability Problems
In this paper, we extend and modify the ERA approach proposed in Ref. 13 to solve Propositional Satisfiability Problems (SATs). The new ERA approach involves a multiagent system where each agent only senses its local environment and applies some self-organizing rules for governing its movements. The environment, which is a two-dimensional cellular environment, records and updates the local values that are computed and affected according to the movements of individual agents. In solving a SAT with the ERA approach, we first divide variables into several groups, and represent each variable group with an agent whose possible positions correspond to the elements in a Cartesian product of variable domains, and then randomly place each agent onto one of its possible positions. Thereafter, the ERA system will keep on dispatching agents to choose their movements until an exact or approximate solution emerges. The experimental results on some benchmark SAT test-sets have shown that the ERA approach can obtain comparable results as well as stable performances for SAT problems. In particular, it can find approximate solutions for SAT problems in only a few steps. The real value of this approach is that it is a distributed asynchronous approach without any centralized control or evaluation, where the agents can cooperate to solve problems without explicit communication.
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.
18067929
Multiagent SAT (MASSAT): Autonomous Pattern Search in Constrained Domains
In this paper, we present an autonomous pattern search approachto solving Satisfiability Problems (SATs). Our approach is essentially a multiagent system. To solve a SAT problem, we first divide variables into groups, and represent each variable group with an agent. Then, we randomly place each agent onto a position in the correspoding local space which is composed of the domains of the variables that are represented by this agent. Thereafter, all agents will autonomously make searchdecisions guided by some reactive rules in their local spaces until a special pattern (i.e., solution) is found or a time step threshold is reached. Experimental results on some benchmark SAT test-sets have shown that by employing the MASSAT approach, we can obtain performances comparable to those of other popular algorithms.
37683026
Web Intelligence (WI)
The 21st century is the age of the Internet and the World Wide Web. The Web revolutionizes the way we gather, process, and use information. At the same time, it also redefines the meanings and processes of business, commerce, marketing, finance, publishing, education, research, development, as well as other aspects of our daily life. The revolution is just beginning. Although individual Web based information systems are constantly being deployed, advanced issues and techniques for developing and for benefiting from Web intelligence still remain to be systematically studied. The article defines a new research field, namely Web Intelligence (WI) by giving a complete picture of WI related topics for systematic study on advanced Web technology and developing Web based intelligent information systems. Roughly speaking, WI exploits AI and advanced information technology on the Web and Internet. It is the key and the most urgent research field of IT for business intelligence.
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.
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.
36178651
The vertex linear arboricity of distance graphs
A distance graph is a graph G(R,D) with the set of all points of the real line as vertex set and two vertices u,[email protected]?R are adjacent if and only if |u-v|@?D where the distance set D is a subset of the positive real numbers. Here, the vertex linear arboricity of G(R,D) is determined when D is an interval between 1 and @d. In particular, the vertex linear arboricity of integer distance graphs G(D) is discussed, too.
656200
Robust distributed node localization with error management
Location knowledge of nodes in a network is essential for many tasks such as routing, cooperative sensing, or service delivery in ad hoc, mobile, or sensor networks. This paper introduces a novel iterative method ILS for node localization starting with a relatively small number of anchor nodes in a large network. At each iteration, nodes are localized using a least-squares based algorithm. The computation is lightweight, fast, and any-time. To prevent error from propagating and accumulating during the iteration, the error control mechanism of the algorithm uses an error registry to select nodes that participate in the localization, based on their relative contribution to the localization accuracy. Simulation results have shown that the active selection strategy significantly mitigates the effect of error propagation. The algorithm has been tested on a network of Berkeley Mica2 motes with ultrasound TOA ranging devices. We have compared the algorithm with more global methods such as MDS-MAP and SDP-based algorithm both in simulation and on real hardware. The iterative localization achieves comparable location accuracy in both cases, compared to the more global methods, and has the advantage of being fully decentralized.
39794072
Three-Dimensional Effects Created by Macromedia Flash MX
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.