Social Capital in Network Organizations
Authors: Saad Alqithami, Henry Hexmoor
AAAI 2014 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | This paper will outline the effect of social capital on a network structure inside a network organization. A main concern of multiagent systems is the coordination of autonomous agents that interact dynamically to achieve their goals. There is a need to develop SC assessment models or mechanisms that can measure qualities among autonomous agents operating in large-scale and open service-oriented organizations. Such mechanisms are required to estimate the future behavior of agents and agents peers in order to simplify the interaction process with those peers. We are striving to overcome these problems with a novel perspective by utilizing a network organization (NO). The aim in the future is to further validate and develop SC models and to produce a method to quantify network organization’s responsiveness. |
| Researcher Affiliation | Academia | Saad Alqithami and Henry Hexmoor Department of Computer Science Southern Illinois University Carbondale, IL 62901 USA {Alqithami, Hexmoor}@siu.edu |
| Pseudocode | No | The paper does not contain any structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide any concrete access to source code for the methodology described. |
| Open Datasets | No | The paper is theoretical and does not use or reference any datasets for training experiments. |
| Dataset Splits | No | The paper is theoretical and does not report on experiments or dataset splits for validation. |
| Hardware Specification | No | The paper describes a conceptual model and does not report on computational experiments, therefore no hardware specifications are mentioned. |
| Software Dependencies | No | The paper describes a conceptual model and does not mention any software dependencies with specific version numbers. |
| Experiment Setup | No | The paper is theoretical and does not describe any experiments or their setup, including hyperparameters or training configurations. |