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IJSTR >> Volume 9 - Issue 8, August 2020 Edition



International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616



Agent Based Computational Modelling For Mapping Of Exact Ksatisfiability Representation In Hopfield Neural Network Model

[Full Text]

 

AUTHOR(S)

Hamza Abubakar, Sagir Abdu Masanawa, Surajo Yusuf, Yusuf Abdurrahman

 

KEYWORDS

Agent base modelling, Artificial Neural network, Hopfield neural network, Optimzation problem, Satisfiability, Exact Satisfiability, logic program.

 

ABSTRACT

Recent studies in the field of machine learning and artificial intelligence (AI) are focusing on developing hybrid models to simplify the complexity involved in the training of the neural network. This form of simplicity is valuable for seeking an established convergence artificial neural network. In this paper, agent-based modelling (ABM) using NETLOGO as a platform has been proposed to facilitate the training process of Hopfield neural modelling in carrying Exact kSatisfiability programming. The developed ABM hybrid model explored the optimal task representing Exact kSatisfiability logic due to the simplicity, flexibility and user-friendly mannerism manifest by ABM model. ABM was used to simulate the process of taking decisions of individual movements, fortification of behaviour, group dynamics, population communications and social interactions within populations. The performance has been displayed based on Global Minimum ratio, local Minimum Ratio, Hamming Distance Mean Square Error and Computation time in evaluating the model performance. The performance of the HN model in carrying Exact kSatisfiability (Exact kSAT) logic was demonstrated good agreement when compared with ordinary kSatisfiability (kSAT).

 

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