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Releases: aika-algorithm/aika-java

v2.0.2-alpha

v2.0.2-alpha Pre-release
Pre-release

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@aika-algorithm aika-algorithm released this 11 Mar 17:27

Pre-release for the AIKA 2.0 version

v1.4.0

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@aika-algorithm aika-algorithm released this 16 Aug 05:20
  • Reduced memory consumption.
  • Implementation to compute the average activation of an activation object over all interpretation options.
  • Linking of interpretation options.

v1.3.0

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@aika-algorithm aika-algorithm released this 31 Jul 16:16
  • Major simplification of the interpretation search.
  • Code reorganization.

v1.2.0

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@aika-algorithm aika-algorithm released this 07 Jun 17:21
  • Removed synapse bias. Bias now depends on the neuron type.
  • Exception Handling refactoring.
  • Removed factory methods.
  • Refactored position propagation.
  • Bugfixes

v1.1.0

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@aika-algorithm aika-algorithm released this 28 Feb 05:07
  • Major cleanup refactoring
  • Bugfixes

v1.0.0

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@aika-algorithm aika-algorithm released this 09 Dec 09:49
  • Bugfixes

v0.25

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@aika-algorithm aika-algorithm released this 02 Dec 17:51
  • Bugfixes

v0.24

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@aika-algorithm aika-algorithm released this 17 Nov 07:54
  • Refactoring of the relation architecture.
  • Bugfixes

v0.23

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@aika-algorithm aika-algorithm released this 14 Nov 17:26
  • The Range class has now been replaced with by a slots concept. Previously, an activation had a range with a begin and an end position. Now activations can possess an arbitrary number of positions.
  • The synapse bias is now used to decide whether a synapse is conjunctive or disjunctive.

v0.22

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@aika-algorithm aika-algorithm released this 31 Oct 04:51
  • API Refactoring: Synapse relations are now established through a separate builder class.
  • The range positions are now optionally variable. This feature is required for text generation. In this
    use case the positions are not known in advance and need to be computed during processing.
  • Introduced passive neurons. Passive neurons are only evaluated if the connected output neuron requires it. Passive neurons act basically like callback functions.
  • Optimization of the interpretation search.
  • Lots of bug fixes.