fixed SingleAction class so that it sets its own reference to its
domain.
Updated GridWorldDomain and its visualizer to supports 1D wall and
locations of multiple types.
Added Visualizer constructor to take as an argument the StateRenderLayer
object it should use.
Added support to Stochastic Games to have a world observer, similar to
the action observer for single agent domains.
added a runtime exception that is thrown when an attribute for an object
is requested that does not exist for the object's object class. This is
more informative than the -1 array list index out-of-bounds exception
that would have been thrown otherwise.
added a Q-value initialization interface for stochastic games naive Q
agents.
renamed some methods in grid world domain
Added LearningRate interface to enable learning algorithms to use
learning rate functions that decay with state in different ways
Added learning rate function for stochastic games
minor updates
Preliminary RBF
AbstractGroundedAction created and learning rate and policy updated to
accomadate
Unified Q-Learning auxiliary tools between stochastic games agent and
single agent by leveraging the abstract grounded action class
added copy constructor to QValue
Updated to include OO-MDP int attribute values that are non-categorical
and boolean (which is treated as a special case of discrete). Updated
discrete hash factory to reflect addition.
Added RLGlue agent and environment support
Added a tabulated domain wrapper
added RLGlue java codec to library since code now supports RLGlue.
Added learning algorithm experiment and performance plotting tools to
streamline work.
updated rbf