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parameters and relationships guiding what the system pays attention to, at what points in time. This is a term inclusive of Importance Updating and Hebbian Learning. • Attentional Currency: Short Term Importance and Long Term Importance values are implemented in terms of two different types of artificial money,
nce. NIPS 2009 Workshop on Deep Learning for Speech Recognition and Related Applications, 2009. Ark09b. Ronald Arkin. Governing Lethal Behavior in Autonomous Robots. Chapman and Hall, 2009. Ar175. P. K. Arlin. Cognitive development in adulthood: A fifth stage?, volume 11. Developmental Psychology, 1975. Artn0
ake our points about glocal knowledge representation in neural net type systems without discussing some aspects of learning in these systems. 13.5.1 Hebbian Learning The most common and plausible assumption about learning in the brain is that synaptic connec- tions between neurons are adapted via some variant of
a view toward providing near-term guidance to military robots (see e.g. Arkin’s excellent though chillingly-titled book Governing Lethal Behavior in Autonomous Robots [Ark09b], the result of US military funded research). However, there are reasonably strong arguments that human values (similarly to e.g. human langu
e parameters and relationships guiding what the system pays attention to, at what points in time. This is a term inclusive of Importance Updating and Hebbian Learning. Attentional Currency: Short Term Importance and Long Term Importance values are implemented in terms of two different types of artificial money, ST
rence. NIPS 2009 Workshop on Deep Learning for Speech Recognition and Related Applications, 2009. ArkO9b. Ronald Arkin. Governing Lethal Behavior in Autonomous Robots. Chapman and Hall, 2009. Arl75. P. K. Arlin. Cognitive development in adulthood: A fifth stage?, volume 11. Developmental Psychology, 1975. Arm04.
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