page_title: Learning classifier system
hierarchical_section_title: Learning classifier system
caption_attribution_description: English: Visualization of LCS rules learning to approximate a 3D function. Each blue ellipse represents an individual rule covering part of the solution space. (Adapted with permission from Martin Butz)
context_page_description: Learning classifier systems, or LCS, are a paradigm of rule-based machine learning methods that combine a discovery component with a learning component. Learning classifier systems seek to identify a set of context-dependent rules that collectively store and apply knowledge in a piecewise manner in order to make predictions. This approach allows complex solution spaces to be broken up into smaller, simpler parts.
  The founding concepts behind learning classifier systems came from attempts to model complex adaptive systems, using rule-based agents to form an artificial cognitive system.
context_section_description: Learning classifier systems, or LCS, are a paradigm of rule-based machine learning methods that combine a discovery component (e.g. typically a genetic algorithm) with a learning component (performing either supervised learning, reinforcement learning, or unsupervised learning).  Learning classifier systems seek to identify a set of context-dependent rules that collectively store and apply knowledge in a piecewise manner in order to make predictions (e.g. behavior modeling, classification, data mining, regression, function approximation, or game strategy).  This approach allows complex solution spaces to be broken up into smaller, simpler parts.
  The founding concepts behind learning classifier systems came from attempts to model complex adaptive systems, using rule-based agents to form an artificial cognitive system (i.e. artificial intelligence).
caption: 2D visualization of LCS rules learning to approximate a 3D function. Each blue ellipse represents an individual rule covering part of the solution space. (Adapted from images taken from XCSF[1] with permission from Martin Butz)
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