Yukio Pegio Gunji

On simultaneous construction of Voronoi diagram and delaunay triangulation by physarum polycephalum

We experimentally demonstrate that both Voronoi diagram and its dual graph Delaunay triangulation are simultaneously constructed — for specific conditions — in cultures of plasmodium, a vegetative state of Physarum polycephalum. Every point of a given planar data set is represented by a tiny mass of plasmodium. The plasmodia spread from their initial locations but, in certain conditions, stop spreading when they encounter plasmodia originated from different locations. Thus space loci not occupied by the plasmodia represent edges of Voronoi diagram of the given planar set. At the same time, the plasmodia originating at neighboring locations form merging protoplasmic tubes, where the strongest tubes approximate Delaunay triangulation of the given planar set. The problems are solved by plasmodium only for limited data sets, however the results presented lay a sound ground for further investigations.

Robot Control with Biological Cells

At present there exists a large gap in size, performance, adaptability and robustness between natural and artificial information processors for performing coherent perception-action tasks under real-time constraints. Even the simplest organisms have an enviable capability of coping with an unknown dynamic environment. Robots, in contrast, are still clumsy if confronted with such complexity. This paper presents a bio-hybrid architecture developed for exploring an alternate approach to the control of autonomous robots. Circuits prepared from amoeboid plasmodia of the slime mold Physarum polycephalum are interfaced with an omnidirectional hexapod robot. Sensory signals from the macro-physical environment of the robot are transduced to cellular scale and processed using the unique micro-physical features of intracellular information processing. Conversely, the response form the cellular computation is amplified to yield a macroscopic output action in the environment mediated through the robots actuators.

Minimal model of a cell connecting amoebic motion and adaptive transport networks

A cell is a minimal self-sustaining system that can move and compute. Previous work has shown that a unicellular slime mold, Physarum, can be utilized as a biological computer based on cytoplasmic flow encapsulated by a membrane. Although the interplay between the modification of the boundary of a cell and the cytoplasmic flow surrounded by the boundary plays a key role in Physarum computing, no model of a cell has been developed to describe this interplay. Here we propose a toy model of a cell that shows amoebic motion and can solve a maze, Steiner minimum tree problem and a spanning tree problem. Only by assuming that cytoplasm is hardened after passing external matter (or softened part) through a cell, the shape of the cell and the cytoplasmic flow can be changed. Without cytoplasm hardening, a cell is easily destroyed. This suggests that cytoplasmic hardening and/or sol-gel transformation caused by external perturbation can keep a cell in a critical state leading to a wide variety of shapes and motion.

An adaptive and robust biological network based on the vacant-particle transportation model

A living system reveals local computing by referring to a whole system beyond the exploration-exploitation dilemma. The slime mold, Physarum polycephalum, uses protoplasmic flow to change its own outer shape, which yields the boundary condition and forms an adaptive and robust network. This observation suggests that the whole Physarum can be represented as a local protoplasmic flow system. Here, we show that a system composed of particles, which move and are modified based upon the particle transformation that contains the relationship between the parts and the whole, can emulate the network formed by Physarum. This system balances the exploration-exploitation trade-off and shows a scale-free sub-domain. By decreasing the number of particles, our model, VP-S, can emulate the Physarum adaptive network as it is attracted to a food stimulus. By increasing the number of particles, our model, VP-D, can emulate the pattern of a growing Physarum. The patterns produced by our model were compared with those of the Physarum pattern quantitatively, which showed that both patterns balance exploration with exploitation. This model should have a wide applicability to study biological collective phenomena in general.

Formal model of internal measurement: alternate changing between recursive definition and domain equation

Abstract We sketch a paradox generally resulting from recursivity, and propose a novel model to express evolutionary processes that requires identification of an interaction with internal measurement. In this model, a paradox is not resolved and the notion of relativity of any resolution is implicit. In a dynamical system a certain transition rule is used recursively along time. If one takes the foundation (or context) of recursivity into consideration, one obtains a fixed point or one confronts a paradox. In order to resolve this paradox, we adopt Scotts technical way to identify the form of a fixed point with a domain equation and to obtain a reflective domain, however we simultaneously show that any resolution is destined to be relative. In utilizing this notion, we construct a model of dynamical process by embedding a measurement process in one time step. Any time transition involves the process of doubting the foundation of a transition rule leading to a fixed point. Solving it and obtaining a reflexive domain is used as a new transition rule. Also, this process perpetually proceeds along time, and then the system perpetually proceeds while any solution is destined to be relative. We illustrate this type of model by using a dynamically changing contraction mapping as the interface of state and transition rule. Finally, we show that one can formalize emergent properties by using this model and discuss the relationship between endo-physics and internal measurement.

Global logic resulting from disequilibration process

Describing a system in which internal detection or observation proceeds at a finite velocity is always destined to end up with a form of self-contradiction. For any formal language, for such a description, we must assume that the velocity of observation propagation or VOP be infinity. In the present paper, we propose a self-referential scheme intended for formally describing a system exhibiting the process of disequilibration propagating at a finite VOP, and find that a global logic can emerge from local disequilibration. Conservative cellular automata of Margolus type, for instance, enable disequilibration to be replaced by such a process that the number of particles is not conserved globally while appearing to be conserved by local observers. One cannot determine local rules universally. Nevertheless, global logic emerges as a result of the dynamics of a one-to-many type mapping. This is a fundamental aspect of natural languages or communication relevant to natural life and intelligence.

Autonomic life as the proof of incompleteness and Lawvere's theorem of fixed point

Abstract If finite velocity of observation propagation is taken into consideration, one is faced with a paradox or infinite regression in his own logic. It is the same as Goedels theorem of incompleteness or Wittgensteins paradox, and in general it can be formally replaced by Lawveres theorem of a fixed point. To describe time evolution under finite velocity of observation propagation is not to construct a new logic in which the paradox can be removed or improved, but to accept the paradox itself. Given a system in which a paradox is deduced by taking the finite velocity of observation propagation, we can regard the whole formal description, which consists of the system and a proof sequence, toward the paradox, as an evolutionary system. A formal evolutionary system defined here is one demonstration of autonomic life.

An associative learning experiment using the plasmodium of Physarum polycephalum

Abstract The plasmodium of Physarum polycephalum is a unicellular and multinuclear giant amoeba that shows adaptive behaviors. To test the presence of memory and learning ability in the plasmodium, we performed an associative learning experiment using the unicellular organism. The plasmodium in this experiment seemed to acquire a reversed thermotactic property, a new preference for the lower temperature. The result implied a possibility of unicellular learning, though in a preliminary way. We also discuss a possible mechanism of learning by the organism.

Robot control: from silicon circuitry to cells

Life-like adaptive behaviour is so far an illusive goal in robot control. A capability to act successfully in a complex, ambiguous, and harsh environment would vastly increase the application domain of robotic devices. Established methods for robot control run up against a complexity barrier, yet living organisms amply demonstrate that this barrier is not a fundamental limitation. To gain an understanding of how the nimble behaviour of organisms can be duplicated in made-for-purpose devices we are exploring the use of biological cells in robot control. This paper describes an experimental setup that interfaces an amoeboid plasmodium of Physarum polycephalum with an omnidirectional hexapod robot to realise an interaction loop between environment and plasticity in control. Through this bio-electronic hybrid architecture the continuous negotiation process between local intracellular reconfiguration on the micro-physical scale and global behaviour of the cell in a macroscale environment can be studied in a device setting.

Beyond input-output computings: Error-driven emergence with parallel non-distributed slime mold computer

The emergence derived from errors is the key importance for both novel computing and novel usage of the computer. In this paper, we propose an implementable experimental plan for the biological computing so as to elicit the emergent property of complex systems. An individual plasmodium of the true slime mold Physarum polycephalum acts in the slime mold computer. Modifying the Elementary Cellular Automaton as it entails the global synchronization problem upon the parallel computing provides the NP-complete problem solved by the slime mold computer. The possibility to solve the problem by giving neither all possible results nor explicit prescription of solution-seeking is discussed. In slime mold computing, the distributivity in the local computing logic can change dynamically, and its parallel non-distributed computing cannot be reduced into the spatial addition of multiple serial computings. The computing system based on exhaustive absence of the super-system may produce, something more than filling the vacancy.