Rich Coalitional Resource Games
Authors: Nicolas Troquard
AAAI 2018 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | The main contributions are a formal link with the existing literature, and complexity results for several classes of models. We investigate a few problems relevant to cooperative games, such as deciding whether a group of agents can form a coalition and act together in a way that satisfies all of them. In terms of solution concepts, we study the computational aspects of the core of a game. WIN is NP-complete for one-goal affine MLL RCRGs and PSPACE-complete for one-goal affine MALL RCRGs. |
| Researcher Affiliation | Academia | Nicolas Troquard The KRDB Research Centre Faculty of Computer Science Free University of Bozen-Bolzano Piazza Domenicani, 3 I-39100 Bozen-Bolzano BZ, Italy |
| Pseudocode | Yes | Algorithm 1 Non deterministic algorithm for WIN |
| Open Source Code | No | The paper is theoretical and does not mention releasing any source code or provide links to a repository. |
| Open Datasets | No | This paper is theoretical and does not involve the use of datasets for training, validation, or testing. |
| Dataset Splits | No | This paper is theoretical and does not involve dataset splits for validation or other experimental purposes. |
| Hardware Specification | No | This paper is purely theoretical and does not report on experimental hardware specifications. |
| Software Dependencies | No | This paper is purely theoretical and does not mention specific software dependencies with version numbers. |
| Experiment Setup | No | This paper is theoretical and does not describe an experimental setup with hyperparameters or training configurations. |