Combinatorial Games with Incomplete Information
Authors: Junkang Li, Bruno Zanuttini, Véronique Ventos
IJCAI 2024 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We propose a minimal generalisation of combinatorial games to incorporate incomplete information, called combinatorial game with incomplete information (CGII). ...we show that computing optimal strategies for CGIIs has the same computational complexity as for general extensive-form games. The results written in bold font are new from this work; the others can be directly deduced from the literature. (This indicates proofs, reductions, and theoretical analysis, not empirical evaluation.) |
| Researcher Affiliation | Collaboration | Junkang Li1,2 , Bruno Zanuttini2 and V eronique Ventos1 1Nukk AI, Paris, France 2Normandie Univ.; UNICAEN, ENSICAEN, CNRS, GREYC, 14 000 Caen, France |
| Pseudocode | No | The paper does not contain structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper provides a link to a long version with proofs ('https: //hal.science/hal-04568854'), not to source code for the described methodology. No other statements about source code availability were found. |
| Open Datasets | No | This paper is theoretical and does not describe experiments using datasets. |
| Dataset Splits | No | This paper is theoretical and does not describe experiments using datasets or requiring data splits. |
| Hardware Specification | No | This paper is theoretical and does not describe experiments requiring hardware specifications. |
| Software Dependencies | No | This paper is theoretical and does not describe experiments requiring specific software dependencies with version numbers. |
| Experiment Setup | No | This paper is theoretical and does not describe experiments requiring an experimental setup. |