Remarkable problem-solving ability of unicellular amoeboid organism and its mechanism

Abstract

Choosing a better move correctly and quickly is a fundamental skill of living organisms that corresponds to solving a computationally demanding problem. A unicellular plasmodium of Physarum polycephalum searches for a solution to the travelling salesman problem (TSP) by changing its shape to minimize the risk of being exposed to aversive light stimuli. In our previous studies, we reported the results on the eight-city TSP solution. In this study, we show that the time taken by plasmodium to find a reasonably high-quality TSP solution grows linearly as the problem size increases from four to eight. Interestingly, the quality of the solution does not degrade despite the explosive expansion of the search space. Formulating a computational model, we show that the linear-time solution can be achieved if the intrinsic dynamics could allocate intracellular resources to grow the plasmodium terminals with a constant rate, even while responding to the stimuli. These results may lead to the development of novel analogue computers enabling approximate solutions of complex optimization problems in linear time.

The Semantic Librarian: A search engine built from vector-space models of semantics

“…We view the difference between traditional and psychologically-inspired cognitive computing to be analogous to the difference between traditional and biologically-inspired engineering in which scientists leverage the lessons and study of natural cognitive systems to solve complex applied problems. For example, Tero et al (2010) studied how slime molds (Physarum polycephalum) develop efficient and fault tolerant transportation networks (see also Zhu, Kim, Hara, & Aono, 2018, for a similar analysis in relation to computing and complex problem solving). They used that knowledge to design a computational method to design and optimize human transportation networks (e.g., rail systems).…”

Amoeba-inspired analog electronic computing system integrating resistance crossbar for solving the travelling salesman problem

“…We focus on a living amoeboid organism that performs trialand-error behaviour to survive efficiently and resiliently in a harsh environment, deforming its gel-like body 30,31 . Here, we demonstrate, as a proof of concept, an analogue electronic computing system called an "electronic amoeba" 32,33 , inspired by the food search and risk avoidance behaviour of a single-celled amoeboid organism, Physarum polycephalum 30,31,[34][35][36][37][38][39] . In the electronic amoeba, an arbitrary TSP instance can be mapped on the resistor network of a crossbar structure shown in Fig.…”

A Circuit-Level Amoeba-Inspired SAT Solver

“…AmbSAT (or AmoebaSAT) [9], [10], which changes multiple variables in parallel at each iteration step. AmbSAT is an SLS solver that is inspired by the complex spatiotemporal dynamics of a single-celled amoeba of the true slime mold Physarum polycephalum, which deforms into optimal shapes to maximize favorable nutrient absorption and minimize the risk of being exposed to aversive light stimuli [11], [12]. For some randomly generated SAT instances, AmbSAT can find solutions to SAT with a much fewer number of iteration steps than WSAT [7], which is a simple SLS solver, because at each iteration step the former can travel a longer distance in the search space than the latter [10], [13].…”