Application of Higher Order Hopfield Network
Neural network and logic integration is the latest trend in Artificial Intelligence. Neural Symbolic Integration is a combination of neural networks’ robust learning capabilities with symbolic knowledge representation, reasoning, and explanation capabilities in ways that retain the strengths of each...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Published: |
ENCON 2013
2013
|
| Subjects: | |
| Online Access: | http://ir.unimas.my/id/eprint/8167/ |
| _version_ | 1848836316770336768 |
|---|---|
| author | Saratha, Sathasivam Ng, Pei Fen Muraly, Velavan |
| author_facet | Saratha, Sathasivam Ng, Pei Fen Muraly, Velavan |
| author_sort | Saratha, Sathasivam |
| building | UNIMAS Institutional Repository |
| collection | Online Access |
| description | Neural network and logic integration is the latest trend in Artificial Intelligence. Neural Symbolic Integration is a combination of neural networks’ robust learning capabilities with symbolic knowledge representation, reasoning, and explanation capabilities in ways that retain the strengths of each paradigm. In this paper, an Agent Based Modelling (ABM) was introduced by using Netlogo which carry out higher order horn clauses in Hopfield network. Our interest in this paper is confined largely to an important class of neural networks that perform useful computations through a process of learning. So, from the ABM that designed, we can carry out some computer simulation to verify and test the ABM develop. |
| first_indexed | 2025-11-15T06:21:50Z |
| format | Article |
| id | unimas-8167 |
| institution | Universiti Malaysia Sarawak |
| institution_category | Local University |
| last_indexed | 2025-11-15T06:21:50Z |
| publishDate | 2013 |
| publisher | ENCON 2013 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | unimas-81672015-07-02T06:30:21Z http://ir.unimas.my/id/eprint/8167/ Application of Higher Order Hopfield Network Saratha, Sathasivam Ng, Pei Fen Muraly, Velavan Q Science (General) Neural network and logic integration is the latest trend in Artificial Intelligence. Neural Symbolic Integration is a combination of neural networks’ robust learning capabilities with symbolic knowledge representation, reasoning, and explanation capabilities in ways that retain the strengths of each paradigm. In this paper, an Agent Based Modelling (ABM) was introduced by using Netlogo which carry out higher order horn clauses in Hopfield network. Our interest in this paper is confined largely to an important class of neural networks that perform useful computations through a process of learning. So, from the ABM that designed, we can carry out some computer simulation to verify and test the ABM develop. ENCON 2013 2013 Article PeerReviewed Saratha, Sathasivam and Ng, Pei Fen and Muraly, Velavan (2013) Application of Higher Order Hopfield Network. ENCON 2015. http://rpsonline.com.sg/proceedings/9789810760595/html/025.xml doi: 10.3850/978-981-07-6059-5_025 |
| spellingShingle | Q Science (General) Saratha, Sathasivam Ng, Pei Fen Muraly, Velavan Application of Higher Order Hopfield Network |
| title | Application of Higher Order Hopfield Network |
| title_full | Application of Higher Order Hopfield Network |
| title_fullStr | Application of Higher Order Hopfield Network |
| title_full_unstemmed | Application of Higher Order Hopfield Network |
| title_short | Application of Higher Order Hopfield Network |
| title_sort | application of higher order hopfield network |
| topic | Q Science (General) |
| url | http://ir.unimas.my/id/eprint/8167/ http://ir.unimas.my/id/eprint/8167/ http://ir.unimas.my/id/eprint/8167/ |