Internet bid systems have been widely used recently. In those systems, the bid price is provided by the seller. When the bid price is set too high compared with the normal price, the successful bid rate can be decreased. Otherwise, when it is set too low based on inaccurate information, it can result in a successful bid with no profit at all. To resolve this problem, we propose an agent that automatically generates bid prices for sellers based on various costing methods such as the high-low point method, the scatter diagram method, and the learning curve method. Through performance experiments, we have found that the number of successful bids with appropriate profit can be increased using the bid pricing agent. Among the costing methods, the learning curve method has shown the best performance. Also, we discuss about how to design and implement the bid pricing agent.