The fuzzy systems handbook: a practitioner's guide to building, using, and maintaining fuzzy systems
The fuzzy systems handbook: a practitioner's guide to building, using, and maintaining fuzzy systems
Fuzzy neural networks with application to sales forecasting
Fuzzy Sets and Systems
Decision-Making of BDI Agents, a Fuzzy Approach
CIT '04 Proceedings of the The Fourth International Conference on Computer and Information Technology
Simulation for the Social Scientist
Simulation for the Social Scientist
Applied Artificial Intelligence
Comment on “Combinatorial rule explosion eliminated by a fuzzy rule configuration” [and reply]
IEEE Transactions on Fuzzy Systems
A systematic design for coping with model risk
Expert Systems with Applications: An International Journal
Proceedings of the 6th ACM India Computing Convention
| Hi-index | 12.05 |
Regulation can play an important role in effectively managing systemic risk while providing accountability to all affected governments. IMF points out weak governance structures as one of the main causes for financial/economical crisis. However, research in this area is still limited. One of the reasons is the inherent complexity of the public sector governance notion. In this research, the regulatory governance of the financial sector is conceived as a complex system, in which governance is perceived as a phenomenon resulting from the interactions among all the actors that influence or are influenced by regulatory activities within the financial sector. An agent-based simulation was developed to analyze and evaluate the emergent behaviors from the governance in the Brazilian finance sector under different macroeconomics variables and different attitudes, perceptions and desires of economic and political actors. The agent-based model is combined with an econometric model, which is intended to characterize the macroeconomic environment. The regulatory environment is modeled by computational agents using BDI (beliefs-desires-intentions) architecture. The agents have beliefs about their environment and desires they want to satisfy, thus leading them to create intentions to act. The agents' behavior was modeled using fuzzy rules built by means of content analysis of newspapers and in-depth interviews with experts from the financial area. Computational experiments demonstrate the potential of the agent-based model simulation in the study of complex environments involving regulatory governance.