The Talmudic exegesis is constructed on special hermeneutic rules which have the logical meaning in fact. On the basis of this circumstance it is possible to speak about a special logical culture of the Talmud and to call the logic used there.

This book shows that the plasmodium of Physarum polycephalum can be considered a natural labelled transition system, and based on this, it proposes high-level programming models for controlling the plasmodium behaviour. The presented programming is a form of pure behaviourism: the authors consider the possibility of simulating all basic stimulus-reaction relations. As plasmodium is a good experimental medium for behaviouristic models, the book applies the programming tools for modelling plasmodia as unconventional computers in different behavioural sciences based on studying the stimulus-reaction relations. The authors examine these relations within the framework of a bio-inspired game theory on plasmodia they have developed i.e. within an experimental game theory, where, on the one hand, all basic definitions are verified in experiments with Physarum polycephalum and Badhamia utricularis and, on the other hand, all basic algorithms are implemented in the object-oriented language for simulations of plasmodia. The results allow the authors to propose that the plasmodium can be a model for concurrent games and context-based games.

This book presents fundamental theoretical results for designing object-oriented programming languages for controlling swarms. It studies the logics of swarm behaviours. According to behaviourism, all behaviours can be controlled or even managed by stimuli in the environment: attractants (motivational reinforcement) and repellents (motivational punishment). At the same time, there are two main stages in reactions to stimuli: sensing (perceiving signals) and motoring (appropriate direct reactions to signals). This book examines the strict limits of behaviourism from the point of view of symbolic logic and algebraic mathematics: how far can animal behaviours be controlled by the topology of stimuli? On the one hand, we can try to design reversible logic gates in which the number of inputs is the same as the number of outputs. In this case, the behaviouristic stimuli are inputs in swarm computing and appropriate reactions at the motoring stage are its outputs. On the other hand, the problem is that even at the sensing stage each unicellular organism can be regarded as a logic gate in which the number of outputs (means of perceiving signals) greatly exceeds the number of inputs (signals).

The Orthodox Christian thought is the most modally rigorous way of inferring. The subject of the book is to investigate possibilities of explicating the Orthodox thought from the viewpoint of analytic philosophy and symbolic logic. The claim that Orthodox thinking is just mystic and illogical is not true. The logical culture of Orthodox Christian thinking is unknown and ununderstandable for the West, although its schemata are very influential in Eastern Europe till now (Marxism-Leninism is just one of their possible instances). This thought can be called totalistic or even totalitarian. For this thought any truth or falsity is necessary. As a result, the whole world is presented as logical and nomothetic and there is no place for contingency.

Knocking on Heaven's Door is the oldest human dream that seems unrealized still. Religious discourse does show the road, but it requires a blind faith in return. In this book logicians try to hear Heaven's Call and to analyze religious discourse. As a result, the notion of religious logic as a part of philosophical logic is introduced. Its tasks are (1) to construct consistent logical systems formalizing religious reasoning that at first sight seems inconsistent (this research is fulfilled within the limits of modal logic, paraconsistent logic and many-valued logic), (2) to carry out an illocutionary analysis of religious discourse (this research is fulfilled in frames of illocutionary logics), and (3) to formalize Ancient and Medieval logical theories used in the theology of an appropriate religion (they could be studied within the limits of unconventional logics, such as non-monotonic logics, non-well-founded logics, etc.).

The notion of swarm intelligence was introduced for describing decentralized and self-organized behaviors of groups of animals. Then this idea was extrapolated to design groups of robots which interact locally to cumulate a collective reaction. Some natural examples of swarms are as follows: ant colonies, bee colonies, fish schooling, bird flocking, horse herding, bacterial colonies, multinucleated giant amoebae Physarum polycephalum, etc. In all these examples, individual agents behave locally with an emergence of their common effect. An intelligent behavior of swarm individuals is explained by the following biological reactions to attractants and repellents. Attractants are biologically active things, such as food pieces or sex pheromones, which attract individuals of swarm. Repellents are biologically active things, such as predators, which repel individuals of swarm. As a consequence, attractants and repellents stimulate the directed movement of swarms towards and away from the stimulus, respectively. It is worth noting that a group of people, such as pedestrians, follow some swarm patterns of flocking or schooling. For instance, humans prefer to avoid a person considered by them as a possible predator and if a substantial part of the group in the situation of escape panic (not less than 5%) changes the direction, then the rest follows the new direction, too. Some swarm patterns are observed among human beings under the conditions of their addictive behavior such as the behavior of alcoholics or gamers. The methodological framework of studying swarm intelligence is represented by unconventional computing, robotics, and cognitive science. In this book we aim to analyze new methodologies involved in studying swarm intelligence. We are going to bring together computer scientists and cognitive scientists dealing with swarm patterns from social bacteria to human beings. This book considers different models of simulating, controlling, and predicting the swarm behavior of different species from social bacteria to humans.

Around the third millennium B.C. in the Fertile Crescent, a world-system with a single world-economy, covering very vast regions, began to form. Mesopotamia became the center of this world-system. This was possible due to the development of common commercial law and logical competence there. The expansion of the world-economy during the Silk Road period from the 4th century B.C. to the early 5th century A.D. across various countries of Eurasia was accompanied by the spread of logical competence, first formed in Mesopotamia, as a mechanism of legal hermeneutics to draw logical conclusions without fallacies. This competence was simultaneously comprehended in different cultures connected by the Great Silk Road - in ancient Greek logic (4th - 2nd centuries B.C.); ancient Chinese proto-logic (5th - 2nd centuries B.C.); Judaic logical hermeneutics (1st - 2nd centuries A.D.); and in Indian-Buddhist logic (2nd - 6th centuries A.D.). The book analyzes the emergence of logic and its spread and early forms of its reflection. Consequently, logical competence is seen not as an innate ability, but as a social practice first established in Mesopotamia. Logic as a science became possible only after the development of logical competence as an accepted social practice. On the other hand, this view is a non-Marxist assessment of the early form of the world-system, centered on international law and logical competence, which made the world-economy and international trade then possible.

Judaic reasoning is discussed from the standpoint of modern logic. Andrew Schumann defines Judaic logic, traces Aristotelian influence on developing Jewish studies in Judaic reasoning, and shows the non-Aristotelian core of fundamentals of Judaic logic. Further, Schumann proposes some modern approaches to understanding and formalizing Judaic reasoning, including Judaic semantics and (non-Aristotelian) syllogistics.

The history of logic and analytic philosophy in Central and Eastern Europe is still known to very few people. As an exception to the rule, only two scientific schools became internationally popular: the Vienna Circle and the Lvov-Warsaw School. Nevertheless, the countries included in this region have not only joint history, but also joint cultural dynamics. This book is a collection of rare material regarding logical and analytic-philosophical traditions in Central and Eastern European countries, covering the period from the late nineteenth century to the early twenty-first century. An encyclopedic feature covers the history of logic and analytic philosophy in all European post-Socialist countries: Albania, Belarus, Bosnia and Herzegovina, Bulgaria, Croatia, Czechia, Eastern Germany, Estonia, Hungary, Latvia, Lithuania, Macedonia, Moldova, Montenegro, Poland, Romania, Russia, Serbia, Slovakia, Slovenia, Ukraine. The cultural and social context of this philosophy is considered as well.

The notion of swarm intelligence was introduced for describing decentralized and self-organized behaviors of groups of animals. Then this idea was extrapolated to design groups of robots which interact locally to cumulate a collective reaction. Some natural examples of swarms are as follows: ant colonies, bee colonies, fish schooling, bird flocking, horse herding, bacterial colonies, multinucleated giant amoebae Physarum polycephalum, etc. In all these examples, individual agents behave locally with an emergence of their common effect. An intelligent behavior of swarm individuals is explained by the following biological reactions to attractants and repellents. Attractants are biologically active things, such as food pieces or sex pheromones, which attract individuals of swarm. Repellents are biologically active things, such as predators, which repel individuals of swarm. As a consequence, attractants and repellents stimulate the directed movement of swarms towards and away from the stimulus, respectively. It is worth noting that a group of people, such as pedestrians, follow some swarm patterns of flocking or schooling. For instance, humans prefer to avoid a person considered by them as a possible predator and if a substantial part of the group in the situation of escape panic (not less than 5%) changes the direction, then the rest follows the new direction, too. Some swarm patterns are observed among human beings under the conditions of their addictive behavior such as the behavior of alcoholics or gamers. The methodological framework of studying swarm intelligence is represented by unconventional computing, robotics, and cognitive science. In this book we aim to analyze new methodologies involved in studying swarm intelligence. We are going to bring together computer scientists and cognitive scientists dealing with swarm patterns from social bacteria to human beings. This book considers different models of simulating, controlling, and predicting the swarm behavior of different species from social bacteria to humans.

This book presents fundamental theoretical results for designing object-oriented programming languages for controlling swarms. It studies the logics of swarm behaviours. According to behaviourism, all behaviours can be controlled or even managed by stimuli in the environment: attractants (motivational reinforcement) and repellents (motivational punishment). At the same time, there are two main stages in reactions to stimuli: sensing (perceiving signals) and motoring (appropriate direct reactions to signals). This book examines the strict limits of behaviourism from the point of view of symbolic logic and algebraic mathematics: how far can animal behaviours be controlled by the topology of stimuli? On the one hand, we can try to design reversible logic gates in which the number of inputs is the same as the number of outputs. In this case, the behaviouristic stimuli are inputs in swarm computing and appropriate reactions at the motoring stage are its outputs. On the other hand, the problem is that even at the sensing stage each unicellular organism can be regarded as a logic gate in which the number of outputs (means of perceiving signals) greatly exceeds the number of inputs (signals).

This book shows that the plasmodium of Physarum polycephalum can be considered a natural labelled transition system, and based on this, it proposes high-level programming models for controlling the plasmodium behaviour. The presented programming is a form of pure behaviourism: the authors consider the possibility of simulating all basic stimulus-reaction relations. As plasmodium is a good experimental medium for behaviouristic models, the book applies the programming tools for modelling plasmodia as unconventional computers in different behavioural sciences based on studying the stimulus-reaction relations. The authors examine these relations within the framework of a bio-inspired game theory on plasmodia they have developed i.e. within an experimental game theory, where, on the one hand, all basic definitions are verified in experiments with Physarum polycephalum and Badhamia utricularis and, on the other hand, all basic algorithms are implemented in the object-oriented language for simulations of plasmodia. The results allow the authors to propose that the plasmodium can be a model for concurrent games and context-based games.