Trembling-Hand Perfection in Extensive-Form Games with Commitment

Authors: Gabriele Farina, Alberto Marchesi, Christian Kroer, Nicola Gatti, Tuomas Sandholm

IJCAI 2018 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Theoretical We initiate the study of equilibrium refinements based on trembling-hand perfection in extensiveform games with commitment strategies... We also prove that determining the existence of a Stackelberg equilibrium refined or not that gives the leader expected value at least ν is NP-hard. This significantly extends prior complexity results that were specific to strong Stackelberg equilibrium.
Researcher Affiliation Academia 1 Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213, USA 2 Politecnico di Milano, Piazza Leonardo da Vinci 32, I-20133, Milan, Italy gfarina@cs.cmu.edu, alberto.marchesi@polimi.it, ckroer@cs.cmu.edu, nicola.gatti@polimi.it, sandholm@cs.cmu.edu
Pseudocode No The paper does not contain any sections explicitly labeled 'Pseudocode' or 'Algorithm', nor are there any structured code-like blocks describing a procedure.
Open Source Code No The paper does not provide any statements about releasing source code or links to a code repository for the methodology described.
Open Datasets No The paper is theoretical and does not report on experiments using datasets. The examples provided (Figure 2 and Figure 3) are conceptual game theory constructions, not empirical datasets with access information.
Dataset Splits No The paper is theoretical and does not perform empirical validation on datasets, thus no dataset split information (training, validation, test) is provided.
Hardware Specification No The paper is theoretical and does not describe any computational experiments that would require specific hardware specifications.
Software Dependencies No The paper is theoretical and does not provide details about specific ancillary software or library versions used for implementation.
Experiment Setup No The paper is theoretical and does not describe an experimental setup with hyperparameters or system-level training settings.