Yoshihito Saito

Diversification of risk based on divided tasks in large-scale software system manufacture

This paper presents a new contract model of risk aversion in large-scale software system manufacture. We consider a situation where ordering party does not order making software directly. Large-scale software consists of some modules. If the scale of a module is biggish, the software can be efficiently developed ordering as divided modules to some software developers. Generally, software developer has some risks as a company, such as, bankruptcy and dishonor. In such situation, it is important for an outsourcer to know how to reduce a rate of risks. In this paper, we propose a new risk diversification method of contracts with software developers in dividable software systems. In our protocol, we employ a payment policy of initial payment of and incentive fee. Then, the payment amount of initial fee is based on the developers credit. Thus, our protocol prevents an outsourcer from risk on the project. Further we propose a distributed task model to reduce time of development. The results of experiments show the effective strategy for ordering party where risk and number of developers change. Our simulation shows that the outsourcer can get much earnings and performance selling/using the software at an early date when the number of modules and developers increase.

Analyses of Task Allocation Based on Credit Constraints

This paper presents a new contract model of trading with outsourcer agents and developer agents in large-scale software system manufacture. We consider a situation where ordering party does not order making software directly. Large-scale software consists of some modules. If the scale of a module is biggish, the software can be efficiently developed ordering as divided modules to some software developers. Generally, software developer has some risks as a company, such as, bankruptcy and dishonor. In such situation, it is important for an outsourcer to know how to reduce a rate of risks. In this paper, we propose a new risk diversification method of contracts with software developers in dividable software systems. In our protocol, we employ a payment policy of initial payment of and incentive fee. Then, the payment amount of initial fee is based on the developer’s credit. Thus, our protocol prevents an outsourcer from risk on the project. Further we propose a distributed task model to reduce time of development. The results of experiments show the effective strategy for ordering party where risk and number of developers change. Our simulation shows that the outsourcer can get much earnings and performance selling/using the software at an early date when the number of modules and developers increase.

Multi-sided Matching Lecture Allocation Mechanism

Elective Subject is one of important issues as education program in University. Students can declare their preferences directly by selecting it. In most of university, to allocate elective subjects to the students, university staffs poll students the lectures they want to take. However, due to the limitation of time and number of staffs, the hearing investigation includes the reason and the intention in which students select the lectures. Some students sometimes take a lecture for their career, for academical interest, and for assimilation of knowledge. However, some students might take the lecture following the crowd and take the lecture as Mickey Mouse. The latter case is undesirable for the higher education. To solve the problem, in this paper, we propose a new multi-step lecture allocation method based on students preferences and university intentions. Our protocol consists of the three steps of negotiations and three types of allocations. (1) The university warns the students who have never take a certain compulsory subject yet. The students can choose whether they attend the lecture or not. If the students answer they attend the lecture, the students are allocated to the lecture by priority. (2) The students inform the university of their reasons to take the lecture. The university allocates the lectures to the students based on their reasons. (3) They negotiate about the exchange of lectures to increase students’ utilities with each student. Our protocol realizes the high performance of allocation compared with brute force algorithm and reducing computational costs compared with optimizations.

Effects of Value-Based Mechanism in Online Advertisement Auction

In recent years, the listing service is widely used in search site such as Yahoo!, Google, and MSN. In the service, advertising fee and advertising order are decided by the auction that is called Generalized Second Price Auction (GSP) and the auction is actually employed in a lot of search service sites. There are a lot of researches on GSP in order to analyze and clarify its feature and advantages. However, in those researches, the advertisement is mutually independent. Additionally, the value of advertisement is not considered. In this paper, we propose a new mechanism based on GSP that is used in advertisement auctions. Each advertisement has some value, because users click the advertisement when it may be useful for them. We analyze the auctioneer’s profit in comparison between normal GSP, normal VCG (Vickrey-Clarke-Groves Mechanism) and our proposed mechanism. The contribution of our research includes to clarify the features and advantages of advertisement auctions and effects to website owner’s profit rate.

Effects of Distributed Ordering Mechanism in Task Allocation

This paper describes a task allocation mechanism and its performance concerned with software developing. In recent years, multiple types of trading are available since the Internet-based commerce has been developing. Electronic commerce handles items trading including goods, information, times, right, tasks. When tasks are traded, players (software developers) bid each task with the valuation estimated by its cost. Auctioneer (outsourcer) allocates tasks to players based on the order of their valuations and he/she pays money to winners in the auction. However, when a software developer fails to develop the project and becomes bankruptcy, the outsourcer has much amount of damages and the risk of chain bankruptcy. To prevent him/her from such situation, we propose a new contract method based on distributed ordering in which the outsourcer allocates distributed tasks to multiple developers. Winners are determined based on valuations and ability where each developer declares. We also show the result of simulations with the rates of bankruptcy and discuss the effective strategy for outsourcer to allocate the tasks.

A Lecture Allocation Method Based on Multi-Leveled Value Model

This paper describes the lecture allocation method and its support system for elective subjects. Students take a lecture for their career, for academical interest, and for assimilation of knowledge in a university. However, some students might take the lecture following the crowd and take the lecture as Mickey Mouse. To solve the problem, we propose a new multi-step lecture allocation method based on students’ preferences and university intentions. Our protocol consists of the three steps of negotiations and three types of allocations. (1) The university warns the students who have never take a certain compulsory subject yet. If the students answer they attend the lecture, the students are allocated to the lecture by priority. (2) The students inform the university of their reasons to take the lecture. The university allocates the lectures to the students based on their reasons. (3) They negotiate about the exchange of lectures to increase students’ utilities with each student. Our protocol realizes the high performance of allocation compared with brute force algorithm and reducing computational costs compared with optimizations.

A Trading Mechanism Based on Interpersonal Relationship in Agent-Based Electronic Commerce

Recently, electronic commerce has been increasing and is also a promising field of applied multiagent technology. In the automated electronic marketplace, agents can trade as buyers and sellers. Buyers and sellers agents evaluate each tradable item with each other, and buy/sell the item. Many electronic commerce sites provide high anonymity for sellers and buyers. Even though there is a special relationship between them such as friends in real world, they generally can not know their individual information in electronic commerce. In actual trade in real world, item’s price is sometimes affected by the relationship between them. This paper focuses on the trading in which buyers and sellers have an asserted relationship such as colleague in a company. This paper analyzes items’ values which is defined by items’ prices and the relationships. Also, we propose a trading protocol including the relationship between sellers and buyers based on the analysis. In the protocol, first, the seller and the buyer evaluate the relationship. Then, the successful trader is determined based on synthesis evaluations. Finally, the seller and successful buyers trade with each other in the calculated price. The Advantage of our protocol is that appropriate evaluations of trading partners can be obtained by various attributes based on Multi-Attribute Utility Theory.

A New Negotiation Mechanism for Agent-Based Lecture Allocation Systems

Elective subject is one of important issues as education program in University. Students can declare their preferences directly by selecting it. In most of university, to allocate elective subjects to the students, university staffs poll students the lectures they want to take. However, due to the limitation of time and number of staffs, the hearing investigation includes the reason and the intention in which students select the lectures. Some students sometimes take a lecture for their career, for academical interest, and for assimilation of knowledge. However, some students might take the lecture following the crowd and take the lecture as Mickey Mouse. The latter case is undesirable for the higher education. To solve the problem, in this paper, we propose a new multi-step lecture allocation method based on students preferences and university intentions. Our protocol has three steps. (1) University warns students who must take a certain lecture to graduate and get a license. (2) Using students preferences, lectures are allocated. (3) Students exchange lectures to increase their intentions and utilities. Our protocol realizes the high performance of allocation compared with brute force algorithm and reducing computational costs compared with optimizations.