Brain-like features of MemComputing machines
arXiv:2302.11403 · doi:10.1109/MOCAST57943.2023.10176728
Abstract
MemComputing is a new model of computation that exploits the non-equilibrium property-we call 'memory'-of any physical system to respond to external perturbations by keeping track of how it has reacted at previous times. Its digital, scalable version maps a finite string of symbols into a finite string of symbols. In this paper, I will discuss some analogies of the operation of MemComputing machines-in general, and digital in particular-with a few physical properties of the biological brain. These analogies could be a source of inspiration to improve on the design of these machines. In turn, they could suggest new directions of study in (computational) neuroscience.
References in corpus (10)
- Colloquium: Criticality and dynamical scaling in living systems
- Memcomputing: a computing paradigm to store and process information on the same physical platform
- Universal Memcomputing Machines
- Polynomial-time solution of prime factorization and NP-hard problems with digital memcomputing machines
- Self-organization and solution of shortest-path optimization problems with memristive networks
- Dynamic Computing Random Access Memory
- Topological field theory and computing with instantons
- Digital Memcomputing: from Logic to Dynamics to Topology
- Critical branching processes in digital memcomputing machines
- Non-equilibrium criticality and efficient exploration of glassy landscapes with memory dynamics