3503340
Organizing synthetic agent behaviors based on a motif architecture
Drawing on our previous work [4], this paper presents an interthreaded motif-based behavioral organiza$on architecture and demonstrates its application in organizing the behaviors of a synthetic agent. The developed architecture enables agent behaviors to be developed as a result of the concurrent self-organization in individual motifs as well as their crisscrossing interactions. The self-organizing motifs contribute to the global organization of agent behaviors through data exchange and control intervention mechanisms along different dimensions of branching threads.
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.
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.
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.
18986222
Concepts and Application of Time-Limiters to High Resolution Schemes
A new class of implicit high-order non-oscillatory time integration schemes is introduced in a method-of-lines framework. These schemes can be used in conjunction with an appropriate spatial discretization scheme for the numerical solution of time dependent conservation equations. The main concept behind these schemes is that the order of accuracy in time is dropped locally in regions where the time evolution of the solution is not smooth. By doing this, an attempt is made at locally satisfying monotonicity conditions, while maintaining a high order of accuracy in most of the solution domain. When a linear high order time integration scheme is used along with a high order spatial discretization, enforcement of monotonicity imposes severe time-step restrictions. We propose to apply limiters to these time-integration schemes, thus making them non-linear. When these new schemes are used with high order spatial discretizations, solutions remain non-oscillatory for much larger time-steps as compared to linear time integration schemes. Numerical results obtained on scalar conservation equations and systems of conservation equations are highly promising.
16633922
Detecting irregularity in videos using kernel estimation and KD trees
Automatic event understanding is the ultimate goal for many visual surveillance systems. In this paper, we propose a novel approach for on-line detecting unusual human activities in videos without the need to explicitly define all valid configurations. Within the framework of Bayesian inference, the detection process is formulated as an MAP estimation where we attempt to find whether activities in new video segments have similar activities in a video database. Our approach has three contributions: firstly, we build the statistical representation of normal behaviors in the database using nonparametric kernel density estimation; secondly, local feature descriptors are highly compressed using PCA and stored in a K-D tree structure, making the search for behavior-based similarity fast and effective; thirdly, the K-D trees are used to generate multiple hypotheses which compete for the optimal classification. The approach requires no tracking, no explicit motion estimation, and no predefined class-based templates. Experimental results have validated our approach in many real-world video sequences.
13217169
New Method for Constructing Isospectral Graphs
There exist several methods available to construct isospectral molecular graphs.l-1° Recently, M. RandiC and his co-workers proposed the ring enlargement process (vide infra) for constructing subspectral graphs.” This method can be also used to construct isospectral graphs; however, it may fail sometimes. For example, the isospectral pair 1, 2 can be enlarged to the isospectral graphs 3,4 shown in Figure 1, where the symbol ‘‘z” signifies an isospectral pair and “-” denotes the ring enlargement procedure. Eigenvalues of 3, 4 are divided into two parts, those in coincidence with that of 1 , 2 are listed on the left, and the remaining ones are put on the right. On the other hand, graph pairs 7, 8 and 9, 10 in Figure 2, yielded from isospectral pair 5, 6, are not isospectral. Noticing the difference of the spectrum of graphs XX, XX’ (by “XX, XX”’ we mean that they are generated from subgraph X in double size by the enlargement procedure, such as 7, 8 from 5; and 9, 10 from a), RandiC suggested that if XX, XX’ are bipartite, they should be isospectral, because all eigenvalues now occur in pairs and the difference between XX and XX’ disappears. Hence, he proposed a conjecture below. CONJECTURE: If graph X yields nonisomorphic bipartite enlargements XX, XX’, etc.; the derived graphs are not only superspectral to the parent graph X but are also mutually cospectral.
2696332
A boosting approach for motif modeling using ChIP-chip data
MOTIVATION
Building an accurate binding model for a transcription factor (TF) is essential to differentiate its true binding targets from those spurious ones. This is an important step toward understanding gene regulation.


RESULTS
This paper describes a boosting approach to modeling TF-DNA binding. Different from the widely used weight matrix model, which predicts TF-DNA binding based on a linear combination of position-specific contributions, our approach builds a TF binding classifier by combining a set of weight matrix based classifiers, thus yielding a non-linear binding decision rule. The proposed approach was applied to the ChIP-chip data of Saccharomyces cerevisiae. When compared with the weight matrix method, our new approach showed significant improvements on the specificity in a majority of cases.
2364475
Combined functional partitioning and communication speed selection for networked voltage-scalable processors
This paper presents a new technique for global energy optimization through coordinated functional partitioning and speed selection for embedded processors interconnected by a high-speed serial bus. Many such serial interfaces are capable of operating at multiple speeds and can open up a new dimension of trade-offs to complement today's CPU-centric voltage scaling techniques for processors. We propose a multi-dimensional dynamic programming formulation for energy-optimal functional partitioning with CPU/communication speed selection for a class of data-regular applications under performance constraints. We demonstrate the effectiveness of our optimization techniques with an image processing application mapped onto a multi-processor architecture with a multi-speed Ethernet.