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020 _a9789819792863
_9978-981-97-9286-3
024 7 _a10.1007/978-981-97-9286-3
_2doi
050 4 _aQ342
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
072 7 _aUYQ
_2thema
100 1 _aShen, Weiran.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_988538
245 1 0 _aAI-Driven Mechanism Design
_h[electronic resource] /
_cby Weiran Shen, Pingzhong Tang, Song Zuo.
250 _a1st ed. 2024.
264 1 _aSingapore :
_bSpringer Nature Singapore :
_bImprint: Springer,
_c2024.
300 _aVIII, 130 p. 31 illus., 17 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aArtificial Intelligence: Foundations, Theory, and Algorithms,
_x2365-306X
505 0 _aChapter 1. Introduction -- Chapter 2. Multi-Dimensional Mechanism Design via AI-Driven Approaches -- Chapter 3. Dynamic Mechanism Design via AI-Driven Approaches -- Chapter 4. Multi-Objective Mechanism Design via AI-Driven Approaches -- Chapter 5. Summary and Future Directions.
520 _aDue to its huge success in industry, mechanism design has been one of the central research topics at the interface of economics and computer science. However, despite decades of effort, there are still numerous challenges, in terms of both theory and applications. These include the problem of how to design mechanisms for selling multiple items, dynamic auctions, and balancing multiple objectives, given the huge design space and buyer strategy space; and the fact that in practice, the most widely applied auction format (the generalized second price auction) is neither truthful nor optimal. Furthermore, many theoretical results are based upon unrealistic assumptions that do not hold in real applications. This book presents the AI-driven mechanism design framework, which aims to provide an alternative way of dealing with these problems. The framework features two abstract models that interact with each other: the agent model and the mechanism model. By combining AI techniques with mechanism design theory, it solves problems that cannot be solved using tools from either domain alone. For example, it can reduce the mechanism space significantly, build more realistic buyer models, and better balance different objectives. The book focuses on several aspects of mechanism design and demonstrates that the framework is useful in both theoretical analysis and practical applications.
650 0 _aComputational intelligence.
_964052
650 0 _aElectronic commerce.
650 0 _aMultiagent systems.
650 0 _aMachine learning.
_955059
650 0 _aGame theory.
650 1 4 _aComputational Intelligence.
_964052
650 2 4 _ae-Commerce and e-Business.
650 2 4 _aMultiagent Systems.
650 2 4 _aMachine Learning.
_955059
650 2 4 _aGame Theory.
700 1 _aTang, Pingzhong.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_988539
700 1 _aZuo, Song.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_988540
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9789819792856
776 0 8 _iPrinted edition:
_z9789819792870
776 0 8 _iPrinted edition:
_z9789819792887
830 0 _aArtificial Intelligence: Foundations, Theory, and Algorithms,
_x2365-306X
_985110
856 4 0 _uhttps://doi.org/10.1007/978-981-97-9286-3
912 _aZDB-2-INR
912 _aZDB-2-SXIT
999 _c65478
_d65478