@article {373,
	title = {Learning in and from brain-based devices.},
	journal = {Science},
	volume = {318},
	year = {2007},
	month = {Nov 16, 2007},
	pages = {1103-5},
	abstract = {<p>
	Biologically based mobile devices have been constructed that differ from robots based on artificial intelligence. These brain-based devices (BBDs) contain simulated brains that autonomously categorize signals from the environment without a priori instruction. Two such BBDs, Darwin VII and Darwin X, are described here. Darwin VII recognizes objects and links categories to behavior through instrumental conditioning. Darwin X puts together the \&quot;what,\&quot;\&quot;when,\&quot; and \&quot;where\&quot; from cues in the environment into an episodic memory that allows it to find a desired target. Although these BBDs are designed to provide insights into how the brain works, their principles may find uses in building hybrid machines. These machines would combine the learning ability of BBDs with explicitly programmed control systems.</p>
},
	author = {GM., Edelman,}
}
@article {382,
	title = {Learning sensory maps with real-world stimuli in real time using a biophysically realistic learning rule},
	journal = {Neural Networks, IEEE Transactions on Neural Networks},
	volume = {13},
	year = {2002},
	month = {May 2002 },
	chapter = {619 - 632 },
	author = {Sanchez-Montanes, M.A. and Peter K{\"o}nig and Paul M.J.F. Verschure}
}
@article {383,
	title = {Layered Control Architectures in Robots and Vertebrates},
	journal = {Adaptive Behavior },
	volume = {7 },
	year = {1999},
	month = {January 1999 },
	chapter = { 99-127 },
	author = {Tony Prescott. and Peter Redgrave, and Kevin Gurney,}
}
