20000085
Toward a Large Scale E-Market: A Greedy and Local Search Based Winner Determination
Combinatorial auction is one of the most popular market mechanisms and it has a huge effect on electronic markets and political strategies. On large scale e-markets, we need a good approximation algorithm for winner determination that is robust for changing the distribution and the number of bids in an auction. We proposed approximate algorithms for combinatorial auctions with massively large number of (more than 100,000) bids. In this paper, we show the robustness of our winner determination algorithms for combinatorial auctions with large number of bids. Experimental results demonstrate that our proposed algorithms are robust on changing the distribution and the number of bids in an auction. Finally, we shortly describe a theoretical limitation about our algorithms that concerns with giving truthfulness of the auction mechanism.
13087182
A Logic-based Framework for Mobile Intelligent Information Agents
Information agents are computational software systems that provides transparent access to many different information sources in the Internet, and to be able to retrieve, analyze, manipulate, and integrate heterogeneous data and information on demand. Mobile agents are an effective choice for many applications to improve latency and bandwidth of client-server applications and to reduce vulnerability to network disconnection. In this paper, we propose MiLog, a logic-based mobile agent framework for constructing intelligent information agents. In the framework, inference and planning process of an agent is written in a compact logic program. A new generation logic program execution engine provides strong migration capability with reasonable execution speed. The framework has been used to develop a web-based decision support system ’BiddingBot’.
35506309
Scheduling Meetings with Distributed Local Consistency Reinforcement
8383423
A Support Method for Qualitative Simulation-Based Learning System
In this paper, we mainly present a support method of our proposed e-learning system. We employ qualitative simulations because this lets the learners understand the conceptual principles in economic dynamics. First, we define some qualitative values employed on simulation graph model that consists of nodes and arcs. Then, we show the support method using our learning system based on qualitative simulation.
37242657
A Strategy-Proof Mechanism Based on Multiple Auction Support Agents
Agent-mediated electronic commerce has recently commanded much attention. Bidding support agents have been studied very extensively. We envision a future in which many people can trade their goods by using a bidding support agent on Internet auctions. In this paper, we formalize a situation in which people are trading their goods on Internet auctions and employing bidding support agents. Then, we prove that people who use a bidding support agent can successively win trades. Also, we prove that the situation in which every people use a bidding support agent can satisfied strategy proofness and Pareto optimality. Further, we present in the situation, unsupported bidders do not make a positive benefit.
9544952
An Approach to Building Mobile Intelligent Agents Based on Anytime Migration
In this paper, we present an implementation of a Java-based framework for building mobile agents : MiLog (Mobile intelligent agents using Logic programming). MiLog provides logic programming and Java programming for developing intelligent agents since it helps users to effectively construct intelligent mechanisms. We address how to realize an anytime migration mechanism, a HTTP(Hyper Text Transfer Protocol)-based communication mechanism among agents, and web service/access mechanism. Anytime migration enables agents to reactively and autonomously migrate from one computer to another. We present practical applications that have been built on MiLog framework. These applications demonstrate that MiLog is an effective tool for developing practical applications based on mobile intelligent agents.
751173
Approximability of Partitioning Graphs with Supply and Demand
Suppose that each vertex of a graph G is either a supply vertex or a demand vertex and is assigned a positive real number, called the supply or the demand. Each demand vertex can receive “power” from at most one supply vertex through edges in G. One thus wishes to partition G into connected components so that each component C either has no supply vertex or has exactly one supply vertex whose supply is at least the sum of demands in C, and wishes to maximize the fulfillment, that is, the sum of demands in all components with supply vertices. This maximization problem is known to be NP-hard even for trees having exactly one supply vertex and strongly NP-hard for general graphs. In this paper, we focus on the approximability of the problem. We first show that the problem is MAXSNP-hard and hence there is no polynomial-time approximation scheme (PTAS) for general graphs unless P=NP. We then present a fully polynomial-time approximation scheme (FPTAS) for series-parallel graphs having exactly one supply vertex. The FPTAS can be easily extended for partial k-trees, that is, graphs with bounded treewidth.
11122815
Algorithms for the Multicolorings of Partial k-Trees
Let each vertex v of a graph G have a positive integer weight ?(v). Then a multicoloring of G is to assign each vertex v a set of ?(v) colors so that any pair of adjacent vertices receive disjoint sets of colors. A partial k-tree is a graph with tree-width bounded by a fixed constant k. This paper presents an algorithm which finds a multicoloring of any given partial k-tree G with the minimum number of colors. The computation time of the algorithm is bounded by a polynomial in the number of vertices and the maximum weight of vertices in G.
204985889
Regular graphs with excess one
Abstract It is shown that there exists no regular graph with excess e =1 and girth 2 r +1⩾5.
2226240
Partitioning Trees of Supply and Demand
Assume that a tree T has a number ns of "supply vertices" and all the other vertices are "demand vertices." Each supply vertex is assigned a positive number called a supply, while each demand vertex is assigned a positive number called a demand. One wish to partition T into exactly ns subtrees by deleting edges from T so that each subtree contains exactly one supply vertex whose supply is no less than the sum of demands of all demand vertices in the subtree. The "partition problem" is a decision problem to ask whether T has such a partition. The "maximum partition problem" is an optimization version of the partition problem. In this paper, we give three algorithms for the problems. First is a linear-time algorithm for the partition problem. Second is a pseudo-polynomial-time algorithm for the maximum partition problem. Third is a fully polynomial-time approximation scheme (FPTAS) for the maximum partition problem.
40835687
Partitioning trees of supply and demand
Assume that a tree T has a number ns of "supply vertices" and all the other vertices are "demand vertices." Each supply vertex is assigned a positive number called a supply, while each demand vertex is assigned a positive number called a demand. One wishes to partition T into exactly ns subtrees by deleting edges from T so that each subtree contains exactly one supply vertex whose supply is no less than the sum of demands of all demand vertices in the subtree. The "partition problem" is a decision problem to ask whether T has such a partition. The "maximum partition problem" is an optimization version of the partition problem. In this paper, we give three algorithms for the problems. The first is a linear-time algorithm for the partition problem. The second is a pseudo-polynomial-time algorithm for the maximum partition problem. The third is a fully polynomial-time approximation scheme (FPTAS) for the maximum partition problem.