- General Info
- Abstract
- Pseudocode
- Source Code
- Installation and Usage
- Citation
- License
- Contact
- Acknowledgement
This repository contains the source code developed and used in the paper: "Advancing Explainable AI with Causal Analysis in Large-Scale Fuzzy Cognitive Maps" written by Marios Tyrovolas, Nikolaos D. Kallimanis, and Chrysostomos Stylios.
In the quest for accurate and interpretable AI models, eXplainable AI (XAI) has become crucial. Among its tools, Fuzzy Cognitive Maps (FCMs) stand out for their ability to exploit both expert knowledge and data-driven insights, providing transparency and intrinsic interpretability. This letter introduces the Total Causal Effect Calculation for FCMs (TCEC-FCM) algorithm, an innovative approach that, for the first time, enables the efficient calculation of total causal effects between concepts in large-scale FCMs by leveraging binary search and Breadth-First Search technique, thereby overcoming the challenge of exhaustive causal path searches that hinder existing methods. Our evaluation across various synthetic FCMs demonstrates TCEC-FCM's superior performance over exhaustive methods, marking a significant advancement in causal effect analysis within FCMs, thus broadening their usability in XAI applications.
Detailed pseudocode for TCEC-FCM-LS and TCEC-FCM-BS Algorithms is provided for a clearer understanding of the implementation:
Complete source code for all algorithms is available, enabling users to explore, test, and apply these methods in various FCM scenarios. Access it in the Source Code folder.
The provided algorithms include:
- TCEC-FCM-LS and TCEC-FCM-BS Algorithms
- DFSB-FCM Algorithm
To use these algorithms, simply ensure you have MATLAB installed on your system, preferably the latest version for optimal compatibility and performance. No additional installation steps are required. Simply download the source code and open it in MATLAB to begin.
While this paper is under review, please cite this work as follows:
Tyrovolas, M., Kallimanis, N. D., & Stylios, C. (2024). Advancing Explainable AI with Causal Analysis in Large-Scale Fuzzy Cognitive Maps. Submitted to IEEE Systems, Man, and Cybernetics Letters
Note: This citation will be updated once the paper is officially published.
This work is licensed under the Creative Commons Attribution-NoDerivatives 4.0 International (CC BY-ND 4.0) License. Under this license, you are free to share and use this work as long as you provide attribution to the original authors and do not modify the material in any way.
For more details, see the full license here.
For any question, please raise an issue or contact
Marios Tyrovolas: tirovolas@kic.uoi.gr
This research has been financed by the European Union: Next Generation EU through the Program Greece 2.0 - National Recovery and Resilience Plan, under the call "Flagship actions in interdisciplinary scientific fields with a special focus on the productive fabric”, project name "Greece4.0 - Network of Excellence for developing, disseminating and implementing digital transformation technologies in Greek Industry" (project code: TAEDR-0535864).