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Rete algorithm
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=== Alpha Network === A possible variation is to introduce additional memories for each intermediate node in the discrimination network. This increases the overhead of the Rete, but may have advantages in situations where rules are dynamically added to or removed from the Rete, making it easier to vary the topology of the discrimination network dynamically. An alternative implementation is described by Doorenbos.<ref>[http://reports-archive.adm.cs.cmu.edu/anon/1995/CMU-CS-95-113.pdf Production Matching for Large Learning Systems] from SCS Technical Report Collection, School of Computer Science, Carnegie Mellon University</ref> In this case, the discrimination network is replaced by a set of memories and an index. The index may be implemented using a [[hash table]]. Each memory holds WMEs that match a single conditional pattern, and the index is used to reference memories by their pattern. This approach is only practical when WMEs represent fixed-length tuples, and the length of each tuple is short (e.g., 3-tuples). In addition, the approach only applies to conditional patterns that perform [[Equality (mathematics)|equality]] tests against [[Variable (mathematics)|constant]] values. When a WME enters the Rete, the index is used to locate a set of memories whose conditional pattern matches the WME attributes, and the WME is then added directly to each of these memories. In itself, this implementation contains no 1-input nodes. However, in order to implement non-equality tests, the Rete may contain additional 1-input node networks through which WMEs are passed before being placed in a memory. Alternatively, non-equality tests may be performed in the beta network described below.
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