A key opportunity of the 21st Century is to merge progress across various science and engineering fields to materialize on the promise of artificial cognition. These interdisciplinary research directions towards cognitive systems may be influenced by the models of the brain and/or rely on a new kind of physical implementation of a mathematical model of cognitive systems. This particular special issue on "Cognitive and Natural Computing with Nanotechnology" was directed to the broad nanomaterials, nanodevice, nanofabrics, nanocircuit, and nanoarchitecture research communities working specifically on novel nanotechnology-enabled directions. The special issue selected papers on innovative ideas for solutions to the principal challenge of realizing architectures that can enable decision-making, intelligent information and sensorial processing, and autonomous learning and adaptation. These systems may employ a variety of fundamental principles and do not necessarily need to emulate the biological or natural automata. Rather, their key distinguishing aspect is that their plasticity, reconfiguration, and functional underpinnings are achieved without involving software. In particular, such systems could 1) introduce new architectural concepts enabled by nanoscale capabilities, resembling the neocortex and natural systems; 2) leverage new materials and nanodevices and their interactions to achieve core cognitive functions; 3) design or build on novel nanofabrics enabling efficient implementation of cognitive computational approaches including achieving high degree of connectivity and collective functions. The ten papers ultimately selected articulate a vision for a cognitive computing direction beyond von Neumann microprocessors and/or present a technology component that contributes to this vision. Nine of these papers appear in this issue and one paper was included in an earlier IEEE Transactions on Nanotechnology (TNANO) issue this year. The nine papers are briefly summarized.
All Science Journal Classification (ASJC) codes
- Computer Science Applications
- Electrical and Electronic Engineering