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There is a collective of locally communicating agents. They believe in some facts of their world. Any agent changes their beliefs depending on the beliefs of their neighbours. Which rules are to be followed? Based on the agent analogy, this paper shows how to extract non‐logical axioms and structural features of the formal doxastic system with temporal instantiation from given inference of a formula, i.e. series of the propositions.

The purpose of this paper is to fill a gap between experimental and abstract‐theoretic models of reaction‐diffusion computing. Chemical reaction‐diffusion computers are amongst leading experimental prototypes in the field of unconventional and nature‐inspired computing. In the reaction‐diffusion computers, the data are represented by concentration profiles of reagents, information is transferred by propagating diffusive and phase waves, computation is implemented in interaction of the traveling patterns, and results of the computation are recorded as a final concentration profile.

The paper analyzes a possibility of co‐algebraic representation of the computation in reaction‐diffusion systems using reaction‐diffusion cellular‐automata models.

Using notions of space‐time trajectories of local domains of a reaction‐diffusion medium the logic of trajectories is built, where well‐formed formulas and their truth‐values are defined by co‐induction. These formulas are non‐well‐founded set‐theoretic objects. It is demonstrated that the logic of trajectories is a co‐algebra.

The paper uses the logic defined to establish a semantical model of the computation in reaction‐diffusion media.

The work presents the first ever attempt toward mathematical formalization of reaction‐diffusion processes and is built building up semantics of reaction‐diffusion computing. It is envisaged that the formalism produced will be used in developing programming techniques of reaction‐diffusion chemical media.

This paper seeks to develop experimental laboratory biological techniques for approximation of existing road networks, optimizing transport links, and designing alternative optimal solutions to current transport problems. It studies how slime mould of Physarum polycephalum approximate highway networks of Brazil.

The 21 most populous urban areas in Brazil are considered and represented with source of nutrients placed in the positions of slime mould growing substrate corresponding to the areas. At the beginning of each experiment slime mould is inoculated in São Paulo area. Slime mould exhibits foraging behavior and spans sources of nutrients (which represent urban areas) with a network of protoplasmic tubes (which approximate vehicular transport networks). The structure of transport networks developed by slime mould are analyzed and compared with families of known proximity graphs. The paper also imitates slime‐mould response to simulated disaster.

It was found that the plasmodium of P. polycephalum develops a minimal approximation of a transport network spanning urban areas. Physarum‐developed network matches man‐made highway network very well. The high degree of similarity is preserved even when high‐demand constraints are placed on repeatability of links in the experiments. Physarum approximates almost all major transport links. In response to a sudden disaster, gradually spreading from its epicenter, the Physarum transport networks react by abandoning transport links affected by disaster zone, enhancement of those unaffected directly by the disaster, massive sprouting from the epicenter, and increase of scouting activity in the regions distant to the epicenter of the disaster.

Experimental methods and computer analysis techniques presented in the paper lay a foundation of novel biological laboratory approaches to imitation and prognostication of socio‐economical developments.

To program cellular automata is to define cell neighbourhood and cell‐state transition rules in order to design an automation which exhibits determined patterns in its evolution or which transforms a given image into another image. In general, a tool for the automatic programming of cellular automata should translate the tuple (source‐configuration) → (target‐configuration) into a set of cell‐state transition rules. This is a problem which has not been completely solved yet. Attempts to show examples of automatic programming of cellular automata using identification algorithms. Results obtained can be used in the design of massively parallel processors with cellular‐automata architecture and a conventional, as well as non‐traditional (e.g. molecular and chemical), elementary base.

The purpose of this paper is to develop experimental laboratory biological techniques for approximation of principle transport networks, optimizing transport links, and developing optimal solutions to current transport problems. It also aims to study how slime mould of Physarum polycephalum approximate autobahn networks in Germany.

The paper considers the 21 most populous urban areas in Germany. It represents these areas with source of nutrients placed in the positions of slime mould growing substrate corresponding to the areas. At the beginning of each experiment slime mould is inoculated in the Berlin area. Slime mould exhibits foraging behavior and spans sources of nutrients (which represent urban areas) with a network of protoplasmic tubes (which approximate vehicular transport networks). The study analyzes structure of transport networks developed by slime mould and compares it with families of known proximity graphs. It also imitates slime‐mould response to simulated disaster by placing sources of chemo‐repellents in the positions of nuclear power plants.

It is found that the plasmodium of Physarum polycephalum develops a minimal approximation of a transport network spanning urban areas. Physarum‐developed network matches autobahn network very well. The high degree of similarity is preserved even when we place high‐demand constraints on repeatability of links in the experiments. Physarum approximates almost all major transport links. In response to a sudden disaster, gradually spreading from its epicenter, the Physarum transport networks react by abandoning transport links affected by disaster zone, enhancement of those unaffected directly by the disaster, massive sprouting from the epicenter, and increase of scouting activity in the regions distant to the epicenter of the disaster.

Experimental methods and computer analysis techniques presented in the paper lay a foundation of novel biological laboratory approaches to imitation and prognostication of socio‐economical developments.

Studies in complexity of cellular automata do usually deal with measures taken on integral dynamics or statistical measures of space‐time configurations. No one has tried to analyze a generative power of cellular‐automaton machines. The purpose of this paper is to fill the gap and develop a basis for future studies in generative complexity of large‐scale spatially extended systems.

Let all but one cell be in alike state in initial configuration of a one‐dimensional cellular automaton. A generative morphological diversity of the cellular automaton is a number of different three‐by‐three cell blocks occurred in the automaton's space‐time configuration.

The paper builds a hierarchy of generative diversity of one‐dimensional cellular automata with binary cell‐states and ternary neighborhoods, discusses necessary conditions for a cell‐state transition rule to be on top of the hierarchy, and studies stability of the hierarchy to initial conditions.

The method developed will be used – in conjunction with other complexity measures – to built a complete complexity maps of one‐ and two‐dimensional cellular automata, and to select and breed local transition functions with highest degree of generative morphological complexity.

The hierarchy built presents the first ever approach to formally characterize generative potential of cellular automata.

Aims to take an atomistic view on emotions, where emotions are seen as discrete entities interacting with one another.

Takes an unconventional route in simulation of mental processes – studying emotions in terms of artificial, abstract, chemical systems, where emotions are seen as chemical species and chemical reactions correspond to rules of emotional interactions.

An affective solution is a theoretical construct which represents emotions spreading and interacting in massive pools of locally interacting entities. Molecules in the affective solution stand for basic emotions: happiness, anger, fear, confusion and sadness, which diffuse and react with each other by quasi‐chemical laws. In computational experiments with affective solutions, in well‐stirred and thin‐layer reactors, uncovers varieties of behavioural modes of emotion interactions.

Tests applicability of affective solutions in an example of emotional abuse therapy.

Natural collective phenomena, for example, the movement of crowds of pedestrians and the impressive nest formations of social insects, provide us with an existence proof that sophisticated constructions may be built by swarms of relatively simple artificial agents. The constructions often appear to have required impressive control and coordination – yet each agent in the collective does not appear to be provided with an internal world model or blue‐print for the complete construction. These macroscopic structures emerge as the consequence of interaction of agents, carrying out simple rules based upon the local state of the world, which includes the interaction between agents and the growing structure. In an attempt to understand the underpinning principles of structure formation in collectives of minimal mobile agents the paper focuses on an investigation of automata‐like agents in a two‐dimensional lattice. All agents start their evolution at the same site on the lattice. Every agent moves at random until it finds a neighbourhood it likes more than other neighbourhoods. The agents form a stationary structure of their immobile bodies. The paper focuses upon the parameterisation of the rule space and the mapping between parameter space and the resulting global structure formed by the agents.