Adaptive Mechanisms


An AdaptiveMechanism is a type of Mechanism that modifies the parameters of one or more other Components. In general, an AdaptiveMechanism receives its input from an ObjectiveMechanism, however this need not be the case. There are three types of AdaptiveMechanism:

See ModulatorySignal for conventions used for the names of Modulatory components.

Creating an AdaptiveMechanism

An AdaptiveMechanism can be created by using the standard Python method of calling the constructor for the desired type. AdaptiveMechanisms of the appropriate subtype are also created automatically when other Components are created that require them, or a form of modulation is specified for them. For example, a ControlMechanism is automatically created as part of a System (for use as its controller), or when control is specified for the parameter of a Mechanism; and one or more LearningMechanism are created when learning is specified for a Process or a System (see the documentation for subtypes of AdaptiveMechanisms for more specific information about how to create them).


An AdaptiveMechanism has the same basic structure as a Mechanism. In addition, every AdaptiveMechanism has a modulation attribute, that determines the default method by which its ModulatorySignals modify the value of the Components that they modulate (see the modulation for a description of how modulation operates, and the documentation for individual subtypes of AdaptiveMechanism for more specific information about their structure and modulatory operation).


LearningMechanism and ControlMechanism are always executed at the end of a TRIAL, after all ProcessingMechanisms in the Process or System to which they belong have been executed; all LearningMechanism executed first, and then ControlMechanism. All modifications made are available during the next TRIAL. GatingMechanism are executed in the same manner as ProcessingMechanisms; however, because they almost invariably introduce recurrent connections, care must be given to their initialization and/or scheduling).

Class Reference

class psyneulink.core.components.mechanisms.adaptive.adaptivemechanism.AdaptiveMechanism_Base(default_variable, size, modulation, params, name, prefs, context, function=None)

Subclass of Mechanism that modulates the value(s) of one or more other Component(s).


AdaptiveMechanism is an abstract class and should NEVER be instantiated by a call to its constructor. They should be instantiated using the constructor for a subclass.


ModulationParam – determines how the output of the AdaptiveMechanism’s ModulatorySignal(s) are used to modulate the value of the State(s) to which their ModulatoryProjection(s) project.