• receiving bids,
• revealing intermediate information, and
• clearing the auction.
• Auction scope refers to the number of distinct types of commodities being traded. The scope is one in most familiar cases, but can be much greater in multicommodity auctions.
• Nature of goods. Each type of good can be discrete or continuous, but most auction research studies the allocation of discrete goods.
• Auction A lists a single unit. The auction uses typical ascending auction rules with a fixed closing time of tA.
• Auction B lists a single unit. The auction is also an ascending auction, but it closes after time tB when δ B time passes without any new bids.
• Auction C lists five units. It uses a type of multi-unit auction in which each bidder pays the price of the lowest accepted bid. This auction closes after time tC when δ C time passes without any new bids.
• A model of the user's preferences. The agent should not ask the user how much he or she values every available model of computer monitor, for example, but should ask a few questions from which it can infer a relatively complete preference structure.
• A list of auctions relevant to the task and a method for determining each auction's rules. Current auction search engines (such as GoTo Auctions http://search.auctions.goto.com/) already let users do keyword searches on multiple auction sites. The widespread adoption of XML ontologies for describing products will simplify the search process and improve results. The auction parameterization I described earlier provides the semantic definitions needed to communicate an auction's rules.
• A model of the other participants in the auctions. We expect market models to range between those that account for each individual agent and those that represent only aggregate behavior.