17801993
Efficiency of emergent constraint satisfaction in small-world and random agent networks
In this paper, we study the efficiency of emergent constraint satisfaction in small-world and random agent networks. We find that emergent constraint satisfaction in a small-world network is less efficient than in some other networks (e.g., regular networks). Further, we find that this finding holds in almost all random networks. Based on these observations, we study the relationship between the efficiency of emergent constraint satisfaction and the randomness of the corresponding network from which the constraint satisfaction problem is generated.
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.
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.
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.
39795223
On the Use of Sender Adaptation to Improve Stability and Fairness for Layered Video Multicast
Layered multicast has been shown as a promising technique for distributing a video program to a potentially large number of heterogeneous receivers. While several layered multicast approaches have been proposed, prior work has almost exclusively focused on improving the perceived video quality in terms of PSNR value or/and the fairness among different receivers. In this paper, we first argue that stability is another major index for the video playback quality; in an extreme case even with the best possible achievable PSNR value, the frequent switching between different layers still can lead to significant quality degradation. We then introduce an end-to-end adaptation framework that improves the stability and fairness for receivers by employing a dynamic layer rate allocation scheme on the sender's side. Specifically, we propose a new metric, called Stability-aware Fairness Index (SFI), which can capture both the stability as well as fairness. We then formulate the optimal layer rate allocation problem with the objective of minimizing the expected SFI for all the receivers in a multicast session, and derive an efficient algorithm to solve the problem. Simulation results demonstrate that our scheme can significantly improve the degree of stability and fairness, thus leading to better video playback quality.
1100335
Power-aware scheduling under timing constraints for mission-critical embedded systems
Power-aware systems are those that must make the best use of available power. They subsume traditional low-power systems in that they must not only minimize power when the budget is low, but also deliver high performance when required. This paper presents a new scheduling technique for supporting the design and evaluation of a class of power-aware systems in mission-critical applications. It satisfies stringent min/max timing and max power constraints. It also makes the best effort to satisfy the min power constraint in an attempt to fully utilize free power or to control power jitter. Experimental results show that our scheduler can improve performance and reduce energy cost simultaneously compared to hand-crafted designs for previous missions. This tool forms the basis of the IMPACCT system-level framework that will enable designers to explore many power-performance trade-offs with confidence.
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.
9841055
3D object retrieval using 2D line drawing and graph based relevance reedback
This paper aims to provide a user-friendly interface for 3D object retrieval. In previous 3D retrieval systems, the user mainly uses two methods to input a query: providing an existing 3D objects, or providing partial shape information of desired objects such as text and 2D shapes. The first method fails when the user does not have a similar 3D object in hand, and the second method cannot sufficiently describe 3D shapes of objects. We believe that the best way is to have a good interface that can convert a 2D sketch drawn by the user into a 3D object as the query. A 2D line drawing is easy to be drawn and is the simplest and most direct way of illustrating a 3D object. In this paper, we develop an interface of 3D object reconstruction from line drawings, which allows the user to draw line drawings of objects with both planar and curved surfaces. In addition, in order to refine the retrieved results, we develop a relevance feedback algorithm based on a novel graph discriminant analysis. Compared with recently published relevance feedback algorithms, our algorithm achieves better retrieval performance.
1410914
Collective problem solving through coordinated reaction
We present a methodology, called Constraint Partition and Coordinated Reaction (CP&CR), for collective, evolutionary problem solving. Problem solving is viewed as an emergent functionality from the evolving process of a group of diverse, interacting, and well-coordinated reactive agents. Cheap and effective search knowledge is extracted from local interactions and embedded in the coordination mechanism. Our domain of problem solving is constraint satisfaction problems. We have applied the methodology to job shop scheduling, an NP-complete constraint satisfaction problem. Experimental results on a benchmark suite of problems show that CP&CR outperformed three other state-of-the-art direct search scheduling techniques, in both efficiency and number of problems solved. In addition, CP&CR was experimentally tested on problems of larger sizes and showed favorable scaling-up characteristics.<<ETX>>