J. Boyan, A. Greenwald, R. Kirby, and J. Reiter. Bidding algorithms for simultaneous auctions. In Proceedings of IJCAI Workshop on Economic Agents, Models, and Mechanisms, pages 1--11, 2001.  Home/Search   Document Details and Download   Summary   Related Articles   Check

....tickets and bid in entertainment auc tions. We conclude with a description of ongoing and planned work. 1 Introduction The trading Agent Competition (TAC) is a market simulation game proposed by Wellman and Wurman [1999] with the first competition held in the summer of 2000 [Stone and Greenwald, 2001]. The second and third TACs [Wellman et al. 2002a; Greenwald, 2003] which were held in the subsequent years, maintained research issues in simultaneous interrelated auction context, and had minor modifications for further research. The fourth competition initiates new research issues in supply ....

....Tampa can have any of 60 (i.e. 5 4 3) possible entertainment ticket al..locations for his trip. b) The travel schedule is dominated by hotel airline allocation, and trading agents rarely extend trips just for more entertainment bonus. The origin of this separation heuristic can be traced back to Greenwald and Royan [2001]. Secondly, the UMBCTAC agent separates the entertainment auctions and handles each independently. This heuristic evolved from observations in the continuous double auction (CDA) Friedman and Rust, 1993; Wurman et al. 1998; Smith et al. 2002] in TAC: a) no globally optimal allocation not ....

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Amy Greenwald and Justin Boyan. Bidding algorithms for simultaneous auctions. In Proceedings of Third ACM Conference on E-Commerce, pages 115-124, Tampa, FL, 2001.

....Most signi cantly as a strong source of inspiration, these competitions have played an important role in my own research [18, 21, 17] Numerous other participants from both competitions have also published articles based on research originally motivated by RoboCup and TAC competitions (e. g [5, 14, 8, 10]) Again, the competition results themselves are not scienti cally conclusive. But the process of competition, including the lessons learned, can be scienti cally valuable. 6 Conclusion RoboCup and TAC are both the focal points for large and growing research communities. The competitions play ....

Amy Greenwald and Justing Boyan. Bidding algorithms for simultaneous auctions. In Proceedings of Third ACM Conference on E-Commerce, pages 115-124, Tampa, FL, 2001.

....decision theoretically optimal decisions given profit predictions for hypothetical future situations . Our approach to profit prediction is based upon four simplifying assumptions: The problem appears computationally difficult in general, but was solved effectively in practice in TAC 00 [8, 21]. An alternative approach would be to abstractly calculate the Bayes Nash equilibrium [9] for the game and play the optimal strategy. We dismissed this approach because of its intractabil 1. Closing prices are somewhat, but only somewhat, predictable. 2. Our own bids do not have an ....

....the upper bound produced by LPsolve prior to the search over the integrality constraints, known as the LP relaxation, can be used as an estimate. The LP relaxation can always be generated very quickly . Note that this is not by any means the only possible formulation of the allocation. [8] studied a fast, heuristic variant and found that it performed extremely well on a collection of large, random allocation problems. 21] used a randomized greedy strategy as a fallback for the cases in which the linear program took too long to solve. Table 1 shows a high level overview of ....

Amy Greenwald and Justing Boyan. Bidding algorithms for simultaneous auctions. In Proceedings of Third ACM Conference on E-Commerce, pages 115--124, Tampa, FL, 2001.

..... Benyoucef et al. 2001] considered a problem of simultaneous negotiations for interdependent goods in multiple markets, and applied a work ow management system to model the negotiation process. Their system helped a user to purchase a combinatorial package of goods in noncombinatorial markets. Boyan et al. 2001] also built a system for simultaneous bidding in multiple auctions; they applied beam search with simple heuristics to the problem of buying complementary goods in di erent auctions. Babaio and Nisan [2001] studied the problem of integrating multiple auctions across a supply chain, and proposed a ....

Justin Boyan, Amy Greenwald, R. Mike Kirby, and Jon Reiter. Bidding algorithms for simultaneous auctions. In Proceedings of the Third acm Conference on Electronic Commerce, pages 115-124, 2001.

....at every bidding opportunity. By using an integer linear programming approach, ATTac 2000 was able to compute optimal final allocations in every game instance during the tournament finals one of only 2 entrants to do so. 2 Most TAC participants used some form of greedy strategy for allocation (Greenwald Stone, 2001). It is computationally feasible to quickly determine the maximum utility achievable by client 1 given a set of purchased goods, move on to client 2 with the remaining goods, etc. However, the greedy strategy can lead to suboptimal solutions. For example, consider 2 clients A and B with identical ....

....with a list of resources that need to be purchased. Using the linear programming package LPsolve , ATTac 2000 is usually able to find the globally optimal solution in under one second on a 650 MHz Pentium II. Note that this is not by any means the only possible formulation of the allocation. Greenwald, Boyan, Kirby, and Reiter (2001) studied a variant and found that it performed extremely well on a collection of large, random allocation problems. The above approach is guaranteed to find the optimal allocation, and usually does so quickly. However, since integer linear programming is an NP complete problem, some inputs can ....

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Greenwald, A., Boyan, J., Kirby, R. M., & Reiter, J. (2001). Bidding algorithms for simultaneous auctions. In Proceedings of Third ACM Conference on E-Commerce, p. to appear.

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J. Boyan, A. Greenwald, R. Kirby, and J. Reiter. Bidding algorithms for simultaneous auctions. In Proceedings of IJCAI Workshop on Economic Agents, Models, and Mechanisms, pages 1--11, 2001.

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J. Boyan, A. Greenwald, R. Kirby, and J. Reiter. Bidding algorithms for simultaneous auctions. In Proceedings of IJCAI Workshop on Economic Agents, Models, and Mechanisms, pages 1--11, 2001.

....The percentage of optimal allocations reported by each agent during the competition, as computed by the TAC organizing team, is listed in Table 6. The general allocation problem (i.e. allocation without TAC s feasible package constraints) is NP hard, as it is equivalent to winner determination [3], which in turn is equivalent to the weighted set packing problem [8] Agent Aggregate Minimum Number ATTac 100.0 100.0 13 13 RoxyBot 100.0 100.0 13 13 Aster 99.6 98.0 9 13 UmbcTAC 99.4 94.5 7 13 T1 98.8 88.8 7 13 DAIHard 98.3 95.1 1 13 ALTA 97.1 90.4 2 13 RiskPro 96.7 ....

J. Boyan, A. Greenwald, R. M. Kirby, and J. Reiter. Bidding algorithms for simultaneous auctions. In Proceedings of IJCAI Workshop on Economic Agents, Models, and Mechanisms, pages 1-11, 2001.

....utility, and (ii) completion determining the optimal quantity of each resource to buy and sell given client preferences, current holdings, and market prices. The allocation problem is equivalent to winner determination, and completion can be reduced to winner determination with reserve prices [5]. For the dimensions of TAC, an optimal solution to the allocation problem is tractable. RoxyBot uses a search algorithm based on A and an intricate set of admissible heuristics to produce optimal allocations. An optimal solution to the completion problem is also tractable, but search times ....

....structure of the TAC problem, we believe our approach is suciently generic to transfer to other practical problems in the realm of on line bidding. For example, our algorithms are not wedded to the assumption of linear utility functions, as are competing integer linear programming solutions [5, 10]. The allocation algorithm embedded in RoxyBot is an A search algorithm, which is well known to be optimal if its heuristics are admissible (see, for example, 8] The structure of the search tree is depicted in Figure 1. At each of the 16 depths, some of the nal pool of goods are assigned ....

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A. Greenwald, J. Boyan, R. M. Kirby, and J. Reiter. Bidding algorithms for simultaneous auctions. In Proceedings of Third ACM Conference on Electronic Commerce, to appear, October 2001.

....to the theater and B the ticket to the symphony, which yields an overall utility of 155. The percentage of optimal allocations reported by each agent during the competition is listed inTable 2. 5 4 The general allocation problem is NP complete, as it is equivalent to winner determination [2], which in turn is equivalent to the weighted set packing problem [5] Moreover, exhaustive search is computationally intractable even with as few as eight clients. 5 This information was provided by the TAC organizing team. 4 Agent Strategy Aggregate Minimum Number ATTac optimal 100.0 ....

J. Boyan, A. Greenwald, R. M. Kirby, and J. Reiter. Bidding algorithms for simultaneous auctions. Manuscript available at www.cs.brown.edu/people/amygreen, December 2000.

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Justin Boyan, Amy Greenwald, R. Mike Kirby, and Jon Reiter. Bidding algorithms for simultaneous auctions. In Proceedings of the Third acm Conference on Electronic Commerce, pages 115-124, 2001.

No context found.

Justin Boyan, Amy Greenwald, R. Mike Kirby, and Jon Reiter. Bidding algorithms for simultaneous auctions. In Proceedings of the Third acm Conference on Electronic Commerce, pages 115--124, 2001.

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