Normative Multiagent Systems: The

Authors: Dynamic

IJCAI 2016 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Theoretical We study two important problems (norm synthesis and norm recognition) related to the autonomy of the entire system and the agents, and characterise the computational complexities of solving these problems. The norm synthesis problem is EXPTIME-complete, with respect to the sizes of the system and the objective formula. The NC1 problem can be decided in PTIME, with respect to the sizes of the system and the set . The NC2 problem is PSPACE-complete, with respect to the sizes of the system and the set .
Researcher Affiliation Academia 1Department of Computer Science, Jinan University, China 2Department of Computer Science, University of Oxford, United Kingdom 3School of Engineering, Computer and Mathematical Sciences, Auckland University of Technology, New Zealand 4Institute for Integrated and Intelligent Systems, Griffith University, Brisbane, Australia
Pseudocode Yes We use pseudocode to describe the transition relation. In the first round, i.e., k = 1, it can be described as follows. In the second round, i.e., k = 2, it can be described as follows.
Open Source Code No The paper does not provide any links to open-source code or state that code is available in supplementary materials.
Open Datasets No The paper describes a conceptual 'business system' as an example (Example 1) to illustrate its theoretical concepts, not as an actual dataset for training or evaluation. No specific dataset is mentioned or made available.
Dataset Splits No The paper does not conduct empirical experiments or use datasets, so there is no mention of training, validation, or test splits.
Hardware Specification No The paper is theoretical and does not involve empirical experiments, so no hardware specifications are mentioned.
Software Dependencies No The paper is theoretical and does not describe software implementation, so no specific software dependencies with version numbers are mentioned.
Experiment Setup No The paper is theoretical and does not describe empirical experiments, so there are no details on experimental setup such as hyperparameters or training configurations.