Abstract
The design of Multi-Attribute Double-Sided Auctions (MADSA) is an important problem being examined in a variety of domains. Despite significant efforts, an ideal compromise between expressiveness of preference representation and the tractability of MADSA mechanisms is still subject to much debate. In this paper, we propose a MADSA mechanism whereby bids are placed in the form of Generalised Additively Independent-Decomposable (GAI-D) utility functions. We show that by applying a set of constraints on the composition of these functions a relaxation of the Kalai bargaining solution becomes tractable for large double-sided markets. Experimental results show that the proposed mechanism provides efficient results when compared to the well known k-priced greedy market mechanism.
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Notes
- 1.
When arbitrating bids k-pricing allocates the bid package defined by the bidder (assuming the vendor has sufficient volume of goods) at a price (P) between the two bids. Specifically, the excess value (difference between buyer offer \(B_o\) and vendor reserve \(V_r\)) is allocated between bidder and vendor according to some ratio k, that is \(P = k \cdot (B_o - V_r) + V_r\) [24].
- 2.
We only discuss non-continuous or call-market mechanisms in this paper.
- 3.
Myerson and Satterthwaite [17] define an ex-post efficient market as one that awards the good to the bidder with a higher valuation (be that seller or buyer).
- 4.
In our testing framework a bid also entails a start time for the parking allocation, these are used to filter possible pairings, this puts limitations on the efficiency of scheduling, a complex issue discussed in detail by Fujiwara et al. [9] and others.
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Harold, C., Chhetri, M.B., Kowalczyk, R. (2019). Approximating Multi-attribute Resource Allocations Using GAI Utility Functions. In: Demazeau, Y., Matson, E., Corchado, J., De la Prieta, F. (eds) Advances in Practical Applications of Survivable Agents and Multi-Agent Systems: The PAAMS Collection. PAAMS 2019. Lecture Notes in Computer Science(), vol 11523. Springer, Cham. https://doi.org/10.1007/978-3-030-24209-1_9
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