This paper presents eMediator, an electronic commerce server prototype that demonstrates ways in which algorithmic support and game-theoretic incentive engineering can jointly improve the efficiency of ecommerce. eAuctionHouse, the configurable auction server, includes a variety of generalized combinatorial auctions and exchanges, pricing schemes, bidding languages, mobile agents, and user support for choosing an auction type. We introduce two new logical bidding languages for combinatorial markets: the XOR bidding language and the OR-of-XORs bidding language. Unlike the traditional OR bidding language, these are fully expressive. They therefore enable the use of the Clarke-Groves pricing mechanism for motivating the bidders to bid truthfully. eAuctionHouse also supports supply/demand curve bidding. eCommitter, the leveled commitment contract optimizer, determines the optimal contract price and decommitting penalties for a variety of leveled commitment contracting mechanisms, taking into account that rational agents will decommit strategically in Nash equilibrium. It also determines the optimal decommitting strategies for any given leveled commitment contract. eExchangeHouse, the safe exchange planner, enables unenforced anonymous exchanges by dividing the exchange into chunks and sequencing those chunks to be delivered safely in alternation between the buyer and the seller.

Market mechanisms play a central role in AI as a coordination tool in multiagent systems and as an application area for algorithm design. Mechanisms where buyers are directly cleared with sellers, and thus do not require an external liquidity provider, are highly desirable for electronic marketplaces for several reasons. In this paper we study the inherent complexity of, and design algorithms for, clearing auctions and reverse auctions with multiple indistinguishable units for sale. We consider settings where bidders express their preferences via price-quantity curves, and settings where the bids are price-quantity pairs. We show that markets with piecewise linear supply/demand curves and non-discriminatory pricing can always be cleared in polynomial time. Surprisingly, if discriminatory pricing is used to clear the market, the problem becomes NP-Complete (even for step function curves). If the price-quantity curves are all linear, then, in most variants, the problem admits a poly-time solution even for discriminatory pricing. When bidders express their preferences with price-quantity pairs, the problem is NP-Complete, but solvable in pseudo-polynomial time. With free disposal, the problem admits a poly-time approximation scheme, but no such approximation scheme is possible without free disposal.

The Internet is quickly changing the way business-to-consumer and business-to-business commerce is conducted in the world. The Electronic Revolution has also spawned a trend of price wars and, in some instances, chaos, because of the zero-sum nature of the electronic channel. The technology has created an opportunity to get beyond the lose--lose nature of single issue price wars by determining sellers' and buyers' preferences across multiple issues and encouraging negotiations, thereby creating possible joint gains for all parties. We develop simple multiple-issue algorithms and heuristics that could be used in electronic auctions and electronic markets, to match businesses to businesses and consumers based on dovetailing underlying interests and preferences. We provide arguments that such dovetailed matches should help stabilize markets and make them more efficient. q 1999 Elsevier Science B.V. All rights reserved. Keywords: Auctions; Electronic markets; Decision support; Negotiation modeling; World wide web; Intelligent agents 1.

Markets are important coordination mechanisms for multiagent systems, and market clearing has become a key application area of AI algorithms. We study optimal clearing in the ubiquitous setting where there are multiple indistinguishable units for sale. The sellers and buyers express their bids via supply/demand curves. Discriminatory pricing leads to greater profit for the party who runs the market than nondiscriminatory pricing. We show that this comes at the cost of computation complexity. For piecewise linear curves we present a fast polynomial-time algorithm for nondiscriminatory clearing, and show that discriminatory clearing is complete (even in a very special case). We then show that in the more restricted setting of linear curves, even discriminatory markets can be cleared fast in polynomial time. Our derivations also uncover the elegant fact that to obtain the optimal discriminatory solution, each buyer's (seller's) price is incremented (decremented) equally from that agent's price in the quantity-unconstrained solution.

limited review. Views or opinions expressed herein do not necessarily represent those of the

limited review. Views or opinions expressed herein do not necessarily represent those of the