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Algorithm for optimal winner determination in combinatorial auctions
  • T. Sandholm
  • Computer Science
    Artif. Intell.
  • 1 February 2002
TLDR
The algorithm allows combinatorial auctions to scale up to significantly larger numbers of items and bids than prior approaches to optimal winner determination by capitalizing on the fact that the space of bids is sparsely populated in practice.
Coalition Structure Generation with Worst Case Guarantees
TLDR
This work presents an algorithm that establishes a tight bound within this minimal amount of search, and shows how to distribute the desired search across self-interested manipulative agents.
Computing the optimal strategy to commit to
TLDR
This paper studies how to compute optimal strategies to commit to under both commitment to pure strategies and commitment to mixed strategies, in both normal-form and Bayesian games.
Clearing algorithms for barter exchange markets: enabling nationwide kidney exchanges
TLDR
This work replaces CPLEX as the clearing algorithm of the Alliance for Paired Donation, one of the leading kidney exchanges, and presents the first algorithm capable of clearing these markets on a nationwide scale.
An Implementation of the Contract Net Protocol Based on Marginal Cost Calculations
TLDR
This paper presents a formalization of the bidding and awarding decision process that was left undefined in the original contract net task allocation protocol, based on marginal cost calculations based on local agent criteria.
When are elections with few candidates hard to manipulate?
TLDR
This article characterize the exact number of candidates for which manipulation becomes hard for the plurality, Borda, STV, Copeland, maximin, veto, plurality with runoff, regular cup, and randomized cup protocols and shows that for simpler manipulation problems, manipulation cannot be hard with few candidates.
Distributed rational decision making
TLDR
This chapter discusses multiagent negotiation in situations where agents may have di erent goals and each agent is trying to maximize its own good without concern for the global good.
Coalitions Among Computationally Bounded Agents
TLDR
A normative, application- and protocol-independent theory of coalitions among bounded-rational agents is devised, and the optimal coalition structure and its stability are significantly affected by the agents' algorithms' performance profiles and the cost of computation.
AWESOME: A general multiagent learning algorithm that converges in self-play and learns a best response against stationary opponents
TLDR
AWESOME is presented, the first algorithm that is guaranteed to have the two properties in games with arbitrary numbers of actions and players and it is still the only algorithm that does so while only relying on observing the other players' actual actions (not their mixed strategies).
CABOB: A Fast Optimal Algorithm for Winner Determination in Combinatorial Auctions
TLDR
CABOB is a sophisticated optimal search algorithm that attempts to capture structure in any instance without making assumptions about the instance distribution, and it uses decomposition techniques, upper and lower bounding, elaborate and dynamically chosen bid-ordering heuristics, and a host of structural observations to do this.
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