Reputation-Aware Continuous Double Auction

Authors: Yuan Liu, Jie Zhang, Han Yu, Chunyan Miao

AAAI 2014 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Theoretical Theoretical analysis proves that RCDA is effective in eliciting truthful bids from buyers and sellers in the presence of possible dishonest behavior from both buyers and sellers.
Researcher Affiliation Academia Yuan Liu Jie Zhang Han Yu Chunyan Miao School of Computer Engineering Nanyang Technological University, Singapore
Pseudocode No The paper describes the mechanism using natural language and mathematical equations, but it does not contain structured pseudocode or algorithm blocks.
Open Source Code No The paper does not provide any concrete access to source code, nor does it mention that code is released or available.
Open Datasets No The paper is theoretical and does not mention the use of any datasets for training, validation, or testing, nor does it provide access information for any public or open datasets.
Dataset Splits No The paper is theoretical and does not involve empirical validation with datasets, therefore it does not provide specific dataset split information for validation.
Hardware Specification No The paper focuses on theoretical analysis and does not describe any specific hardware used for experiments.
Software Dependencies No The paper is theoretical and does not provide details about specific ancillary software or library versions needed for replication.
Experiment Setup No The paper is theoretical and does not describe an experimental setup, hyperparameters, or training configurations.