Package | Description |
---|---|
net.sourceforge.jabm.learning |
A library of algorithms for individual learning.
|
net.sourceforge.jabm.strategy |
Classes representing the strategies used by the agents in the simulation.
|
Class and Description |
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AbstractLearner |
ActionSelector
An action selection policy for a reinforcement-learning algorithm.
|
ContinuousLearner
A learning algorithm that outputs a continuous signal.
|
DiscreteLearner
A learner that learns a discrete number of different actions.
|
Learner
Classes implementing this interface indicate that they implement a learning
algorithm.
|
LearnerMonitor |
MDPLearner
Classes implementing this interface implement learning algorithms for Markoff
descision processes (MDPs).
|
MimicryLearner
A learner that attempts to adjust its output to match a training signal.
|
QLearner
An implementation of the Q-learning algorithm.
|
RothErevLearner
A class implementing the Roth-Erev learning algorithm.
|
SelfKnowledgable
Classes implementing this interface indicate that they know if their output
is good enough to be used.
|
StimuliResponseLearner
Classes implementing this interface implement myopic stimuli-response
reinformcement learning algorithms.
|
WidrowHoffLearner
An implementation of the Widrow-Hoff learning algorithm for 1-dimensional
training sets.
|
Class and Description |
---|
MDPLearner
Classes implementing this interface implement learning algorithms for Markoff
descision processes (MDPs).
|
StimuliResponseLearner
Classes implementing this interface implement myopic stimuli-response
reinformcement learning algorithms.
|
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