We present a neural-competitive learning model of language evolution in which several symbol sequences compete to signify a given propositional meaning. Both symbol sequences and p...
The complexity, variation, and change of human languages makes evident the importance of representation and learning in the acquisition and evolution of language. For example, anal...
Yoosook Lee, Travis C. Collier, Gregory M. Kobele,...
Reusable adaptation specifications for adaptive behaviour has come to the forefront of adaptive research recently, with EU projects such as GRAPPLE1, and PhD research efforts on de...
Alexandra I. Cristea, David Smits, Jon Bevan, Maur...
Information extraction (IE) systems are costly to build because they require development texts, parsing tools, and specialized dictionaries for each application domain and each na...
The current period of IT development is characterized by an explosive growth of diverse information representation languages. Applying integration and composition of heterogeneous ...
Leonid A. Kalinichenko, Sergey A. Stupnikov, Nikol...