Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in [1].
Endogenous Energy Reactive Modules Games: Modelling Side Payments among Resource-Bounded Agents
Authors: Julian Gutierrez, David Hyland, Muhammad Najib, Giuseppe Perelli, Michael Wooldridge
IJCAI 2024 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We introduce Energy Reactive Modules Games (ERMGs), an extension of Reactive Modules Games (RMGs) in which actions incur an energy cost (which may be positive or negative), and the choices that players make are restricted by the energy available to them. ... We begin by studying rational verification for ERMGs and then introduce Endogenous ERMGs, where agents can choose to transfer their energy to other agents. ... We study the decision problem of whether a stable outcome exists under both the Nash equilibrium and Core solution concepts. |
| Researcher Affiliation | Academia | Julian Gutierrez1 , David Hyland2 , Muhammad Najib3 , Giuseppe Perelli4 and Michael Wooldridge2 1Monash University 2University of Oxford 3Heriot-Watt University 4Sapienza University of Rome |
| Pseudocode | No | The paper includes 'Figure 1: A Reactive Module', which defines the structure of a module with syntax. However, this is a formal definition and diagram of a system component, not an algorithm or pseudocode detailing a procedure. |
| Open Source Code | No | The paper does not provide any statement or link indicating that source code for the described methodology is publicly available. |
| Open Datasets | No | The paper is theoretical and focuses on formal game models and complexity analysis. It does not involve empirical training on datasets or discuss dataset availability for such purposes. |
| Dataset Splits | No | The paper is theoretical and does not discuss data splitting for validation or provide specific details on how data would be partitioned for model validation. |
| Hardware Specification | No | The paper is theoretical and does not describe any specific hardware (e.g., GPU, CPU models, or server configurations) used for its analysis or computational work. |
| Software Dependencies | No | The paper references formal logics and theoretical frameworks (e.g., 'classical propositional logic', 'Linear Temporal Logic (LTL)', 'Simple Reactive Modules Language (SRML)') but does not list any specific software, libraries, or tools with version numbers that would be required for replication. |
| Experiment Setup | No | The paper describes theoretical models and problem definitions rather than an experimental setup. It does not provide details such as hyperparameters, training configurations, or system-level settings. |