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.
15889327
Towards Better Approximation of Winner Determination for Combinatorial Auctions with Large Number of Bids
We propose new approximate algorithms for combinatorial auctions with massively large number of (more than 100,000) bids. In this paper, we focus on a more practical approximated algorithm in the context of revenue maximization. We propose a hill-climbing greedy algorithm, a SA-like random search algorithm, and their enhancement for searching multiple key parameter values. The experimental results demonstrate that our algorithms perform approximately 0.997 optimality compared with the optimal solutions and better than previously presented approximated algorithms. We also demonstrate that our algorithms are a kind of anytime algorithm that bring better results in shorter computational time that can be applied to large and dynamic electronic markets.
18603528
A Qualitative-Quantitative Methods-Based e-Learning Support System in Economic Education
This paper describes a new qualitative-quantitative simulator to help buyers learn how to make decisions when they purchase goods. In this paper, we propose an e-learning support system (LSDM) for assisting user decision making by applying artificial intelligence technology. When buyers purchase expensive items, they must carefully select these items from many alternatives. The learning support system provides useful information that assists consumers in purchasing goods. We employ qualitative simulations because the output simulation results are useful. Our system consists of a qualitative processing system and a quantitative calculation system. When users use the system, they first input information on the goods they want to purchase. The information input by users is used in the qualitative simulation. Next, they supply the details of their budgets, the rate of loans, and several other factors, on a form. The system then integrates the results of simulation and the user's input data and proposes plans to aid in their decision process. The system has several advantages: it can be used by simple input, the process of simulation is easy to understand, users can learn how to make decisions by trial and error, and the users can base their decision making on synthetic results.
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’.
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.
10045838
Algorithms for finding distance-edge-colorings of graphs
For a bounded integer @?, we wish to color all edges of a graph G so that any two edges within distance @? have different colors. Such a coloring is called a distance-edge-coloring or an @?-edge-coloring of G. The distance-edge-coloring problem is to compute the minimum number of colors required for a distance-edge-coloring of a given graph G. A partial k-tree is a graph with tree-width bounded by a fixed constant k. We first present a polynomial-time exact algorithm to solve the problem for partial k-trees, and then give a polynomial-time 2-approximation algorithm for planar graphs.
13514702
Partitioning a Multi-weighted Graph to Connected Subgraphs of Almost Uniform Size
Assume that each vertex of a graph G is assigned a constant number q of nonnegative integer weights, and that q pairs of nonnegative integers li and ui, 1 ≤i ≤q, are given. One wishes to partition G into connected components by deleting edges from G so that the total i-th weights of all vertices in each component is at least li and at most ui for each index i, 1 ≤i ≤q. The problem of finding such a “uniform” partition is NP-hard for series-parallel graphs, and is strongly NP-hard for general graphs even for q = 1. In this paper we show that the problem and many variants can be solved in pseudo-polynomial time for series-parallel graphs. Our algorithms for series-parallel graphs can be extended for partial k-trees, that is, graphs with bounded tree-width.
32325022
Algorithms for Finding Distance-Edge-Colorings of Graphs
For a bounded integer l, we wish to color all edges of a graph G so that any two edges within distance l have different colors. Such a coloring is called a distance-edge-coloring or an l-edge-coloring of G. The distance-edge-coloring problem is to compute the minimum number of colors required for a distance-edge-coloring of a given graph G. A partial k-tree is a graph with tree-width bounded by a fixed constant k. We first present a polynomial-time exact algorithm to solve the problem for partial k-trees, and then give a polynomial-time 2-approximation algorithm for planar graphs.
3208882
Partitioning a Weighted Graph to Connected Subgraphs of Almost Uniform Size
Assume that each vertex of a graph G is assigned a nonnegative integer weight and that l and u are nonnegative integers. One wish to partition G into connected components by deleting edges from G so that the total weight of each component is at least l and at most u. Such an “almost uniform” partition is called an $(l, u) \mbox{-}$partition. We deal with three problems to find an $(l, u) \mbox{-}$partition of a given graph. The minimum partition problem is to find an $(l, u) \mbox{-}$partition with the minimum number of components. The maximum partition problem is defined similarly. The p-partition problem is to find an $(l, u) \mbox{-}$partition with a fixed number p of components. All these problems are NP-complete or NP-hard even for series-parallel graphs. In this paper we show that both the minimum partition problem and the maximum partition problem can be solved in time O(u4n) and the p-partition problem can be solved in time O(p2u4n) for any series-parallel graph of n vertices. The algorithms can be easily extended for partial k-trees, that is, graphs with bounded tree-width.
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.