Andrew Schumann – författare

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.

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.

The question arises whether logic was given to us by God or whether it is the result of human evolution. I believe that at least the modus ponens rule ( A and if A then B implies B) is inherent in humans, but probably many other modern systems (e.g., resource logic, non - monotonic logic etc.) are the result of humans adapating to the environment. It is therefore of interest to study and compare the way logic is used in ancient cultures as well as the way logic is going to be used in our 21st century. This welcome book studies and compares the way formation of logic in three cultures: Ancient Greek (4th century B.C.), Judaic (1st century B.C. – 1st century A.D.) and Indo-Buddhist (2nd century A.D.) The book notes that logic became especially popular during the period of late antiquity in countries covered by the international trade of the Silk Road. This study makes a valuable contribution to the history of logic and to the very understanding of the origions and nature of logical thinking. -Prof. Dov Gabbay, King''s College London, UK

Andrew Schumann in his book demonsrates that logic step-by-step arose in different places and cultural circles. He argues that if we apply a structural-genealogical method, as well as turn to various sources, particularly, religious, philosophical, linguistic, etc., then we can obtain a more general and more adequate picture of emengence and development of logic. This book is a new and very valuable contribution to the history of logic as a manifestation of the human mind. - Prof. Jan Wolenski, Jagiellonian University, Poland

The author of the Archaeology of Logic defends the claim, calling it "logic is aftter all", which sees logical competence as a practical skill that people began to learn in antiquity, as soom as they realized that avoiding cognitive biases in their reasoning would make their daily activities more successful. The in-depth reading of the book with its diving into the comparative quotations in the long dead or hardly known to most of us languages like Sumerian-Akkadian, Aramatic, Hebrew and etc, will be rewarded by the response that the logical competence is diverse and it can be trained, despite the inevitabilitiy of the reasoning fallacies; and that critical discussions and agaonal character of the social lide are the necessary tools for that. - Prof. Elena Lisanyuk

The question arises whether logic was given to us by God or whether it is the result of human evolution. I believe that at least the modus ponens rule ( A and if A then B implies B) is inherent in humans, but probably many other modern systems (e.g., resource logic, non - monotonic logic etc.) are the result of humans adapating to the environment. It is therefore of interest to study and compare the way logic is used in ancient cultures as well as the way logic is going to be used in our 21st century. This welcome book studies and compares the way formation of logic in three cultures: Ancient Greek (4th century B.C.), Judaic (1st century B.C. – 1st century A.D.) and Indo-Buddhist (2nd century A.D.) The book notes that logic became especially popular during the period of late antiquity in countries covered by the international trade of the Silk Road. This study makes a valuable contribution to the history of logic and to the very understanding of the origions and nature of logical thinking. -Prof. Dov Gabbay, King''s College London, UK

Andrew Schumann in his book demonsrates that logic step-by-step arose in different places and cultural circles. He argues that if we apply a structural-genealogical method, as well as turn to various sources, particularly, religious, philosophical, linguistic, etc., then we can obtain a more general and more adequate picture of emengence and development of logic. This book is a new and very valuable contribution to the history of logic as a manifestation of the human mind. - Prof. Jan Wolenski, Jagiellonian University, Poland

The author of the Archaeology of Logic defends the claim, calling it "logic is aftter all", which sees logical competence as a practical skill that people began to learn in antiquity, as soom as they realized that avoiding cognitive biases in their reasoning would make their daily activities more successful. The in-depth reading of the book with its diving into the comparative quotations in the long dead or hardly known to most of us languages like Sumerian-Akkadian, Aramatic, Hebrew and etc, will be rewarded by the response that the logical competence is diverse and it can be trained, despite the inevitabilitiy of the reasoning fallacies; and that critical discussions and agaonal character of the social lide are the necessary tools for that. - Prof. Elena Lisanyuk

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 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.

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.