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.
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.
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.
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.
16397904
A suite of web-based programs to search for transcriptional regulatory motifs
The identification of regulatory motifs is important for the study of gene expression. Here we present a suite of programs that we have developed to search for regulatory sequence motifs: (i) BioProspector, a Gibbs-sampling-based program for predicting regulatory motifs from co-regulated genes in prokaryotes or lower eukaryotes; (ii) CompareProspector, an extension to BioProspector which incorporates comparative genomics features to be used for higher eukaryotes; (iii) MDscan, a program for finding protein-DNA interaction sites from ChIP-on-chip targets. All three programs examine a group of sequences that may share common regulatory motifs and output a list of putative motifs as position-specific probability matrices, the individual sites used to construct the motifs and the location of each site on the input sequences. The web servers and executables can be accessed at http://seqmotifs.stanford.edu.
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.
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>>
2139488
Projection method III: Spatial discretization on the staggered grid
In E & Liu (SIAM J Numer. Anal., 1995), we studied convergence and the structure of the error for several projection methods when the spatial variable was kept continuous (we call this the semi-discrete case). In this paper, we address similar questions for the fully discrete case when the spatial variables are discretized using a staggered grid. We prove that the numerical solution in velocity has full accuracy up to the boundary, despite the fact that there are numerical boundary layers present in the semi-discrete solutions.
986436
Convergence of gauge method for incompressible flow
A new formulation, a gauge formulation of the incompressible Navier-Stokes equations in terms of an auxiliary field a and a gauge variable Φ, u = a + ⊇Φ, was proposed recently by E and Liu. This paper provides a theoretical analysis of their formulation and verifies the computational advantages. We discuss the implicit gauge method, which uses backward Euler or Crank-Nicolson in time discretization. However, the boundary conditions for the auxiliary field a are implemented explicitly (vertical extrapolation). The resulting momentum equation is decoupled from the kinematic equation, and the computational cost is reduced to solving a standard heat and Poisson equation. Moreover, such explicit boundary conditions for the auxiliary field a will be shown to be unconditionally stable for Stokes equations. For the full nonlinear Navier-Stokes equations the time stepping constraint is reduced to the standard CFL constraint Δt/Δx < C. We also prove first order convergence of the gauge method when we use MAC grids as our spatial discretization. The optimal error estimate for the velocity field is also obtained.