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Open Access Publications from the University of California

Memristor-based Bionic Decision-making Circuit Inspired by Self-awareness


Advancing intelligent systems requires efficient computational architectures built on emerging electronic computing devices, as well as effective biomimetic function simulation to improve overall intelligence. Here we design a memristor-based circuit inspired by self-awareness concepts. It effectively achieves bionic adaptive decision-making by mimicking habituation learning mechanisms. Memristors serve as foundational units in the circuit, facilitating the simulation of functions akin to biological neurons and synapses. They help implement key features such as information filtering, integration, and synaptic plasticity through concise circuit structures and efficient computing methods. Experimental results indicate that our circuit is capable of rapid and efficient information processing through in-memory analog computing, and it can make more reasonable and intelligent adaptive decisions by incorporating self-awareness concepts and biomimetic mechanisms. Extending this work to large-scale decision-making systems holds potential for intelligent platforms aiming to achieve advanced cognitive capabilities.

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