192 Int. J. Bio-Inspired Computation, Vol. 6, No. 3, 2014 Copyright © 2014 Inderscience Enterprises Ltd. A catalytic neuro-fuzzy approach to model agent-based simulation for ombudsman (Lokpal) Praveen Ranjan Srivastava* Information Technology and Systems Area, Indian Institute of Management (IIM), Rohtak, Haryana, 124001, India E-mail: praveenrsrivastava@gmail.com *Corresponding author Saurabh Verma and Shivam Upadhyay Department of Computer Science and Information Systems, Birla Institute of Technology and Science (BITS), Room No. 1142K, Pilani, Rajasthan, India E-mail: saurabhdec1988@gmail.com E-mail: research.shivam@gmail.com Abstract: To live a better life, every citizen requires a clean, honest, dutiful society wherein people do value the integrity of one another and perform their work judiciously but the prevailing corruption and lack of transparency in governance, private or public organisations, educational institutions and related offices which are setup to help common people to avail their rightful services has aroused dissatisfaction among the citizens of the country. People are facing problems when they approach corrupted offices and are forced to bribe the officials to get their work done. To pacify this situation which is eating up the nation slowly and steadily people are willing to set up a Lokpal, an autonomous agency that will not only heed to the appeal by the citizens when they face or observe corruption in local/regional/national government/public bodies but also check for it and take necessary actions. In context with this necessity, this paper proposes an agent-based simulation tool using neural network and fuzzy to understand under what conditions a simple model of the Lokpal agency will be effective. Certain metrics, various scenarios, working conditions and different environment under the organisation is working has been simulated to evaluate their respective effectiveness. Keywords: metrics; scenario attributes; weights; working conditions; severity; centroid formula; decision; opinion metric; attribute metric; working conditions metric; fuzzy; neural network; ombudsman; agent-based simulation; bio-inspired computation. Reference to this paper should be made as follows: Srivastava, P.R., Verma, S. and Upadhyay, S. (2014) ‘A catalytic neuro-fuzzy approach to model agent-based simulation for ombudsman (Lokpal)’, Int. J. Bio-Inspired Computation, Vol. 6, No. 3, pp.192–204. Biographical notes: Praveen Ranjan Srivastava is working as an Assistant Professor in the Information Technology and Systems Group at the Indian Institute of Management (IIM), Rohtak, India. He is currently doing research in the area of software management and decision science. His research areas are software validation, quality management, effort management, software release management, expert system and advanced soft computing techniques. He has published more than 120 research papers in various leading international journals and conferences in the area of software engineering and management. His prime research area is software validation. He is an Editor-in-Chief of the International Journal of Software Engineering Application and Technology (IJSEAT), published by Inderscience. He is also a member of editorial board of various leading journals. Saurabh Verma is a graduate student presently doing his ME in Software Systems at the Department of Computer Science at Birla Institute of Technology and Science, Pilani, India. His areas of interest are in software quality assurance, software architecture, cloud computing, and computer networks. Shivam Upadhyay is a graduate student presently doing his ME in Software Systems at Birla Institute of Technology and Science, Pilani, India. His areas of interest are in database management system, software architecture, object oriented analysis and design and software engineering and management.