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Ascending multi-item auctions

Ascending multi-item auctions. Increase prices until each item is demanded only once Item prices vs. bundle prices E.g. where there exist no appropriate item prices Discriminatory vs. nondiscriminatory prices. Automated bid elicitation. in combinatorial auctions

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Ascending multi-item auctions

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  1. Ascending multi-item auctions • Increase prices until each item is demanded only once • Item prices vs. bundle prices • E.g. where there exist no appropriate item prices • Discriminatory vs. nondiscriminatory prices

  2. Automated bid elicitation in combinatorial auctions [Conen & Sandholm IJCAI-01 workshop; ACM-Ecommerce-01; AAAI-02; Hudson & Sandholm -02]

  3. Another complex problem in combinatorial auctions: “The revelation problem” • Bidders may need to bid on all 2#items combinations • Need to compute the valuation for each combination • Each valuation computation can be NP-complete • For example if a carrier company bids on trucking tasks: TRACONET [Sandholm AAAI-93] • Need to communicate the bids • Need to reveal the bids • Loss of privacy & strategic info

  4. Approaches for tackling the revelation problem • Classic single-shot full revelation mechanims (Vickrey-Clarke-Groves) • Exponentially many valuations revealed • Ascending mechanisms with price feedback (iBundle, [Parkes et al 1999] , akBa [Wurman et al. 2000] , etc.) • Can save revelation • Need exponential revelation in worst case [Nisan 2001] • Our new approach: an elicitor “agent” • Knows things that individual bidders don’t (others’ bids so far) • Asks non-redundant questions from bidders to focus their revelation • Can save revelation • Exponential revelation in worst case [Nisan 2001] • Could be combined with price feedback mechanisms

  5. Our Query Types for Elicitation • Value information: What is your valuation for bundle A? (Answer: Exact or Bounds) • Extensions: • More and more refined answers over times • Bounds in the queries • Order information: Which bundle do you prefer, A or B? • Rank information: • What is the rank of bundle b? • What bundle is at rank x? • Given bundle b, what is the next lower (higher) ranked bundle? • We designed a host of elicitation algorithms that use these query types in different combinations and with different query policies

  6. Example elicitation experiment with random non-redundant value queries only With free disposal Number of bundle values asked / number of bundles Random (nonredundant) elicitor Best elicitor developed so far Advantage of elicitation also holds as the number of agents grows

  7. Incentive compatibility • Elicitor’s questions leak information about others’ preferences • Can be made incentive compatible in weaker equilibrium notions • Ask enough questions to determine Clarke tax prices (#agents+1 “elicitors”) • Could interleave these “extra” questions with real questions • To avoid lazyness; Not necessary from an incentive perspective • Agents don’t have to answer the questions & may answer questions that were not asked • Unlike in ascending “price feedback” auction mechanisms

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