We give a new, implemented approach for automating the negotiation of business contracts. We use our previous work on developing a declarative language for expressing and reasoning about contracts and negotiations. Here we newly extend it to include a knowledge base of rules about negotiation structures and auctions. This work addresses three important research questions. First, how can we represent information to allow automatic inference of negotiation structures? Second, how can we automate negotiations in a way that will closely drive a realistic automated platform (the Michigan Internet AuctionBot)? Third, how can we use auction results to form a final contract? We use our work on Courteous Logic Programs, a form of logic-based knowledge representation, as a way to express fully-specified, executable contracts and extend this to also express partially-specified contracts that are in the midst of being negotiated. In our current prototype, we have developed concepts and vocabulary to reason about several aspects of the negotiation process: (1) high-level knowledge about alternative negotiation structures, (2) general-case rules about auction parameters, (3) rules map the auction parameters to a specific auction platform (the Michigan Intemet AuctionBot), and (4) special-case rules specific domains, including rules from potential buyers and sellers about capabilities, constraints, and preferences. By performing inferencing on the rule sets and interfacing to our auction server, our prototype is able to automatically configure a set of auctions, the results of which will "fill in the blanks" of a partial contract. We use an upcoming Trading Agent Competition as an example domain and are able to automatically generate all the auctions used in the competition (and other possible configurations) starting from a formal description of the competition domain. The result of this project is an extended approach which allows both the automation of the negotiation process, includes conducting of auctions, and produces contracts with are themselves executable using rulebased techniques.