Bidirectional Associative Memories for Adaptive Rule Based Systems
In this paper we present an algorithm for rule based systems that uses Bidirectional Associative Memories (BAMs) to memorize the inputs and their corresponding outputs, and outputs and their corresponding inputs of the system. Adaptive rule based system are becoming very important because rule based...
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| Format: | Article |
| Language: | English |
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EduSoft publishing
2019-04-01
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| Series: | Brain: Broad Research in Artificial Intelligence and Neuroscience |
| Subjects: | |
| Online Access: | https://www.edusoft.ro/brain/index.php/brain/article/view/906/1056 |
| _version_ | 1797990531368747008 |
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| author | Nabil M. Hewahi |
| author_facet | Nabil M. Hewahi |
| author_sort | Nabil M. Hewahi |
| collection | DOAJ |
| description | In this paper we present an algorithm for rule based systems that uses Bidirectional Associative Memories (BAMs) to memorize the inputs and their corresponding outputs, and outputs and their corresponding inputs of the system. Adaptive rule based system are becoming very important because rule based systems are now used in many applications. One drawback of current adaptive rule based systems is that these systems care only about forward chaining mechanism which diminish their performance. Because most of the applications that use rule based systems follow the forward chaining, adaption attempts which is concerned with predicting the inputs given the output is almost null, but this does not eliminate the importance of backward chaining since it is used in too many applications. To tackle this problem we propose a new algorithm that utilizes the good theoretical ground of BAMs to memorize and adapt rules in rule based systems. The main difference between the proposed algorithm and other algorithms is that the proposed algorithm is simple to code the rules and adapt them. In addition, because BAMs supports bi-directions, the proposed algorithm is the only algorithm with adaptation that is able to expect what conditions should be true if we provide the system with outputs. The proposed algorithm considers "and" and "or" rules in the used rules, whereas in all the previous systems, only "and" relation is considered. The proposed solution will be useful in adapting any rule based system whether it uses forward chaining or backward chaining, which is considered to be a significant contribution. The proposed algorithm has six parts; cod table creation, input and output vectors construction, weight matrix calculation, procedure to test the system, procedure to run the proposed algorithm and finally rule extraction or what we call rule code decoding. To illustrate parts of the proposed algorithm, a simple example is provided. |
| first_indexed | 2024-04-11T08:37:03Z |
| format | Article |
| id | doaj.art-c2cdabb726d448c293a5ecaad9c56550 |
| institution | Directory Open Access Journal |
| issn | 2067-3957 |
| language | English |
| last_indexed | 2024-04-11T08:37:03Z |
| publishDate | 2019-04-01 |
| publisher | EduSoft publishing |
| record_format | Article |
| series | Brain: Broad Research in Artificial Intelligence and Neuroscience |
| spelling | doaj.art-c2cdabb726d448c293a5ecaad9c565502022-12-22T04:34:18ZengEduSoft publishingBrain: Broad Research in Artificial Intelligence and Neuroscience2067-39572019-04-011027484Bidirectional Associative Memories for Adaptive Rule Based SystemsNabil M. Hewahi0Department of Computer Science College of Information Technology, University of Bahrain Bahrain International Circuit, Zallaq, Bahrain Phone: +973 1743 8888 nhewahi@uob.edu.bhIn this paper we present an algorithm for rule based systems that uses Bidirectional Associative Memories (BAMs) to memorize the inputs and their corresponding outputs, and outputs and their corresponding inputs of the system. Adaptive rule based system are becoming very important because rule based systems are now used in many applications. One drawback of current adaptive rule based systems is that these systems care only about forward chaining mechanism which diminish their performance. Because most of the applications that use rule based systems follow the forward chaining, adaption attempts which is concerned with predicting the inputs given the output is almost null, but this does not eliminate the importance of backward chaining since it is used in too many applications. To tackle this problem we propose a new algorithm that utilizes the good theoretical ground of BAMs to memorize and adapt rules in rule based systems. The main difference between the proposed algorithm and other algorithms is that the proposed algorithm is simple to code the rules and adapt them. In addition, because BAMs supports bi-directions, the proposed algorithm is the only algorithm with adaptation that is able to expect what conditions should be true if we provide the system with outputs. The proposed algorithm considers "and" and "or" rules in the used rules, whereas in all the previous systems, only "and" relation is considered. The proposed solution will be useful in adapting any rule based system whether it uses forward chaining or backward chaining, which is considered to be a significant contribution. The proposed algorithm has six parts; cod table creation, input and output vectors construction, weight matrix calculation, procedure to test the system, procedure to run the proposed algorithm and finally rule extraction or what we call rule code decoding. To illustrate parts of the proposed algorithm, a simple example is provided.https://www.edusoft.ro/brain/index.php/brain/article/view/906/1056rule based systemsadaptive systemsbidirectional associative memories |
| spellingShingle | Nabil M. Hewahi Bidirectional Associative Memories for Adaptive Rule Based Systems Brain: Broad Research in Artificial Intelligence and Neuroscience rule based systems adaptive systems bidirectional associative memories |
| title | Bidirectional Associative Memories for Adaptive Rule Based Systems |
| title_full | Bidirectional Associative Memories for Adaptive Rule Based Systems |
| title_fullStr | Bidirectional Associative Memories for Adaptive Rule Based Systems |
| title_full_unstemmed | Bidirectional Associative Memories for Adaptive Rule Based Systems |
| title_short | Bidirectional Associative Memories for Adaptive Rule Based Systems |
| title_sort | bidirectional associative memories for adaptive rule based systems |
| topic | rule based systems adaptive systems bidirectional associative memories |
| url | https://www.edusoft.ro/brain/index.php/brain/article/view/906/1056 |
| work_keys_str_mv | AT nabilmhewahi bidirectionalassociativememoriesforadaptiverulebasedsystems |