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 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

This book defines the emerging field of Active Perception which calls for studying perception coupled with action. It is devoted to technical problems related to the design and analysis of intelligent systems possessing perception such as the existing biological organisms and the "seeing" machines of the future. Since the appearance of the first technical results on active vision, researchers began to realize that perception -- and intelligence in general -- is not transcendental and disembodied. It is becoming clear that in the effort to build intelligent visual systems, consideration must be given to the fact that perception is intimately related to the physiology of the perceiver and the tasks that it performs. This viewpoint -- known as Purposive, Qualitative, or Animate Vision -- is the natural evolution of the principles of Active Vision. The seven chapters in this volume present various aspects of active perception, ranging from general principles and methodological matters to technical issues related to navigation, manipulation, recognition, learning, planning, reasoning, and topics related to the neurophysiology of intelligent systems.

Autonomous Mobile Robots: Planning, Navigation, and Simulation presents detailed coverage of the domain of robotics in motion planning and associated topics in navigation. This book covers numerous base planning methods from diverse schools of learning, including deliberative planning methods, reactive planning methods, task planning methods, fusion of different methods, and cognitive architectures. It is a good resource for doing initial project work in robotics, providing an overview, methods and simulation software in one resource. For more advanced readers, it presents a variety of planning algorithms to choose from, presenting the tradeoffs between the algorithms to ascertain a good choice. Finally, the book presents fusion mechanisms to design hybrid algorithms. Presents intuitive and practical coverage of all sub-problems of mobile robotics to enable easy comprehension of sophisticated modern-day robots Covers a wide variety of motion planning algorithms, giving a near-exhaustive treatment of the domain with thought provoking comparisons between algorithms Dives into detailed discussions on robot operating systems and other simulators to get hands-on knowledge without the need of in-house robots

A Physarum machine is a programmable amorphous biological computer experimentally implemented in the vegetative state of true slime mould Physarum polycephalum. It comprises an amorphous yellowish mass with networks of protoplasmic veins, programmed by spatial configurations of attracting and repelling gradients. This book demonstrates how to create experimental Physarum machines for computational geometry and optimization, distributed manipulation and transportation, and general-purpose computation. Being very cheap to make and easy to maintain, the machine also functions on a wide range of substrates and in a broad scope of environmental conditions. As such a Physarum machine is a 'green' and environmentally friendly unconventional computer. The book is readily accessible to a nonprofessional reader, and is a priceless source of experimental tips and inventive theoretical ideas for anyone who is inspired by novel and emerging non-silicon computers and robots. An account on Physarum Machines can be viewed at http: //www.youtube.com/user/PhysarumMachines.