The Dollar Auction with Spiteful Players
Authors: Marcin Waniek, Long Tran-Thanh, Tomasz Michalak, Nicholas Jennings
AAAI 2017 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | In this paper, we analyse the course of an auction when participating players are spiteful, i.e., they are motivated not only by their own profit, but also by the desire to hurt the opponent. We investigate this model for the complete information setting, both for the standard scenario and for the situation where auction starts with nonzero bids. Our results give us insight into the possible effects of meanness onto conflict escalation. [...] Theorem 1. Assume that both players participating in the dollar auction are strongly spiteful, i.e., αi, αj 1 2. It is optimal for both of them to use the malicious strategy. Proof. The following two lemmas will be used in the proof. |
| Researcher Affiliation | Academia | Marcin Waniek University of Warsaw vua@mimuw.edu.pl; Long Tran-Thanh University of Southampton ltt08r@ecs.soton.ac.uk; Tomasz P. Michalak University of Oxford & University of Warsaw tomasz.michalak@cs.ox.ac.uk; Nicholas R. Jennings Imperial College London n.jennings@imperial.ac.uk |
| Pseudocode | No | The paper does not contain any structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide any statement or link regarding the availability of open-source code for the described methodology. |
| Open Datasets | No | This is a theoretical paper, and as such, it does not involve training data or datasets. |
| Dataset Splits | No | This is a theoretical paper, and as such, it does not involve validation datasets or splits. |
| Hardware Specification | No | This is a theoretical paper that focuses on mathematical modeling and analysis. It does not describe any experimental setup or hardware used for running computations. |
| Software Dependencies | No | This is a theoretical paper focused on mathematical modeling. It does not mention any specific software dependencies with version numbers for reproducing experiments. |
| Experiment Setup | No | This is a theoretical paper presenting mathematical models and proofs. It does not involve experimental setups, hyperparameters, or training configurations. |