1, E-Commernce Support System based on Users' Preferences
2, An e-Learning Support System based on Qualitative Simulations for Assisting ConsumersŐ Decision Making

1, Designs on Designated Type Auctions based on Nomination Values
Internet is becoming an increasingly prosperous network for many types of commerce. Internet auctions represent a particularly effective form of electronic commerce and have become a promising field for applying agent technologies. In this research, we employ a designated bid reverse auction based on the item's quality and buyers select items based on their preferences in which they want to purchase in our auction. In the reverse auction multiple sellers compete on goods and the evaluation value shown by the buyer. A designated bidding system is required by the public works office of Japan, and is one form of reverse auction. In designated bidding, since the auctioneer nominates a bidder based on the quality of their work, it can prevent poor companies from making a successful bid prior to bidding. The result of an auctioneer's examination of the standard of technical requirements, the right to bid is granted only to bidders accepted by aptitude.

We extend the current mechanism and propose novel auction mechanisms. In our auction, first, sellers show their capacities in an auction. Next, buyers select sellers with evaluation value(nomination value) for each seller based on the capacities. After that, nominated sellers bid their evaluation values and only one seller offering the lowest value can trade with a buyer.

2, An e-Learning Support System based on Qualitative Simulations for Assisting ConsumersŐ Decision Making
We propose an e-learning support system (LSDM) for assisting a buyers' decision making by applying artificial intelligence technology. When buyers purchase an expensive item, they must carefully select it from many alternatives. The learning support system provides useful information that helps consumers to purchase goods. We employed qualitative simulations because the result of output of simulation is useful. It consists of a qualitative processing system and a quantitative calculation system. When buyers use the system, they first input goods information they want to purchase. The information input by buyers is used in the qualitative simulation. Next, they fill out a form concerned with the details of their budgets, the rate of loans, and several other factors. After that, the system integrates the results of simulation and the buyer's input data and proposes plans to help their decision process. The system has several advantages: buyers can use it by simple input on the Internet, they can understand process of simulation, and they can base their decision making on synthetic results.

Shintani lab. 2004