This article posits the idea of robot learning as a new subfield. The
results of the Robolearn-96 Workshop provide evidence that learning in
modern robotics is distinct from traditional machine learning. The ar
ticle examines the role of robotics in the social and natural sciences
and the potential impact of learning on robotics, generating both a c
ontinuum of research issues and a description of the divergent termino
logy, target domains, and standards of proof associated with robot lea
rning. The article argues that although robot learning is a new subfie
ld, there is significant potential for synergy with traditional machin
e learning if the differences in research cultures can be overcome.