Strategyproof Mechanisms for Friends and Enemies Games

Authors: Michele Flammini, Bojana Kodric, Giovanna Varricchio1950-1957

AAAI 2020 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Theoretical We investigate strategyproof mechanisms for Friends and Enemies Games... We provide strategyproof mechanisms for both settings. More precisely, for FA we first present a deterministic napproximation mechanism, and then show that a much better result can be accomplished by resorting to randomization. Namely, we provide a randomized mechanism whose expected approximation ratio is 4, and arbitrarily close to 4 with high probability. For EA, we give a simple (1 + 2)napproximation mechanism, and show that its performance is asymptotically tight by proving that it is NP-hard to approximate the optimal solution within O(n1 ε) for any fixed ε > 0.
Researcher Affiliation Academia Michele Flammini, Bojana Kodric, Giovanna Varricchio Gran Sasso Science Institute, L Aquila, Italy {michele.flammini, bojana.kodric, giovanna.varricchio}@gssi.it
Pseudocode Yes Mechanism M4. Given an EA preference profile d, M4 1. enumerates the agents in N from 1 up to n; 2. sets C = ; 3. for i = 1 up to n if there exists j > i in the neighborhood of i in G d not matched yet, then C = C {i, j}, otherwise, C = C {i}; 4. returns C.
Open Source Code No The paper does not provide any explicit statements or links indicating that the source code for the methodology is openly available.
Open Datasets No The paper focuses on theoretical mechanisms and their approximation ratios, and does not involve experimental training on datasets.
Dataset Splits No The paper is theoretical and does not describe experiments with dataset splits for training, validation, or testing.
Hardware Specification No The paper describes theoretical mechanisms and their analysis, and does not involve experimental procedures that would require hardware specifications.
Software Dependencies No The paper is theoretical and does not mention any specific software dependencies or versions.
Experiment Setup No The paper is theoretical and does not include details on experimental setup or parameters.