Evolution: From Big Bang to Nanorobots

The present volume is the fourth issue of the Yearbook series entitled ‘Evolution’. The title of the present volume is ‘From Big Bang to Nanorobots’. In this way we demonstrate that all phases of evolution and Big History are covered in the articles of the present Yearbook. Several articles also present the forecasts about future development. The main objective of our Yearbook as well as of the previous issues is the creation of a unified interdisciplinary field of research in which the scientists specializing in different disciplines could work within the framework of unified or similar paradigms, using the common terminology and searching for common rules, tendencies and regularities. At the same time for the formation of such an integrated field one should use all available opportunities: theories, laws and methods. In the present volume, a number of such approaches are used

Evolution: From Big Bang to Nanorobots

The present volume is the fourth issue of the Yearbook series entitled ‘Evolution’. The title of the present volume is ‘From Big Bang to Nanorobots’. In this way we demonstrate that all phases of evolution and Big History are covered in the articles of the present Yearbook. Several articles also present the forecasts about future development. The main objective of our Yearbook as well as of the previous issues is the creation of a unified interdisciplinary field of research in which the scientists specializing in different disciplines could work within the framework of unified or similar paradigms, using the common terminology and searching for common rules, tendencies and regularities. At the same time for the formation of such an integrated field one should use all available opportunities: theories, laws and methods. In the present volume, a number of such approaches are used

Technological Dimension of Big History and the Cybernetic Revolution

The present paper analyzes the evolution of technology from the beginning of the human history. A new paradigm to analyze the causes and trends of the global evolution is introduced. We also describe the direction of technological transformations, discuss and explain the present and forthcoming technological changes. Our analysis of technological evolution mainly focuses on the second half of the 20th century. We present a detailed analysis of the latest technological revolution which we denote as 'Сybernetic', and give some forecasts about its development up to the end of the 21st century. It is shown that the development of various self-regulating systems will be the main trend of this revolution. We argue that the technological transition of the final phase of the Cybernetic Revolution will start in medicine, which is to be the keystone of technological convergence forming the system of MANBRIC-technologies (based on medicine, additive, nano-, bio-, robotic, IT and cognitive technologies). Today we are at the threshold of post-human revolution, the era of an intensive impact on the human body. The authors consider the directions of this revolution such as considerable life extension, organ replacement, BCIs, robotics, genome editing, etc. It is very important to understand the mechanisms of technological development and to measure the possible risks arising from them

Modeling the Molecular Communication Nanonetworks

Nanotechnology is a cutting edge investigation area that has come out with new and unlimited applications. The recent explosion of research in this field, combined with important discoveries in molecular biology have created a new interest in bio-nanorobotic communication. This thesis provides a general theoretical understanding of nanonetworks and their multiple possibilities. It describes some basic concepts of architectures that compose nanotechnology topologies, as well as possible designs for the tiny nanonetwork components, the nanomachines. The thesis also reviews some promising methods proposed for communicating and coordinating in these nanonetworks. Molecular communication applied to nanonetworks presents indeed extremely appealing features in terms of energy consumption, reliability and robustness. Nevertheless, it remains to understand the impact of the extremely slow propagation of molecules and the highly variable environments. As a totally unexplored research area, it is important to establish thorough theoretical framework so that the applications and possible solutions can be validated. It is clear that many issues still need to be addressed in order to understand the limiting performance of information communications among nano-scale devices and design optimal and quasi-optimal encoding/decoding strategies. Such issues are believed to be of key relevance for allowing nanotechnologies display their full potential

Terminating Distributed Construction of Shapes and Patterns in a Fair Solution of Automata

In this work, we consider a solution of automata similar to Population Protocols and Network Constructors. The au-tomata, also called nodes, move passively in a well-mixed solution and can cooperate by interacting in pairs. Dur-ing every such interaction, the nodes, apart from updating their states, may also choose to connect to each other in order to start forming some required structure. The model introduced here is a more applied version of Network Con-structors, imposing geometrical constraints on the permissi-ble connections. Each node can connect to other nodes only via a very limited number of local ports, which implies that at any given time it has only a bounded number of neigh-bors. Connections are always made at unit distance and are perpendicular to connections of neighboring ports. Thoug

Multi Agent Systems

Research on multi-agent systems is enlarging our future technical capabilities as humans and as an intelligent society. During recent years many effective applications have been implemented and are part of our daily life. These applications have agent-based models and methods as an important ingredient. Markets, finance world, robotics, medical technology, social negotiation, video games, big-data science, etc. are some of the branches where the knowledge gained through multi-agent simulations is necessary and where new software engineering tools are continuously created and tested in order to reach an effective technology transfer to impact our lives. This book brings together researchers working in several fields that cover the techniques, the challenges and the applications of multi-agent systems in a wide variety of aspects related to learning algorithms for different devices such as vehicles, robots and drones, computational optimization to reach a more efficient energy distribution in power grids and the use of social networks and decision strategies applied to the smart learning and education environments in emergent countries. We hope that this book can be useful and become a guide or reference to an audience interested in the developments and applications of multi-agent systems

When less is more: Robot swarms adapt better to changes with constrained communication

To effectively perform collective monitoring of dynamic environments, a robot swarm needs to adapt to changes by processing the latest information and discarding outdated beliefs. We show that in a swarm composed of robots relying on local sensing, adaptation is better achieved if the robots have a shorter rather than longer communication range. This result is in contrast with the widespread belief that more communication links always improve the information exchange on a network. We tasked robots with reaching agreement on the best option currently available in their operating environment. We propose a variety of behaviors composed of reactive rules to process environmental and social information. Our study focuses on simple behaviors based on the voter model—a well-known minimal protocol to regulate social interactions—that can be implemented in minimalistic machines. Although different from each other, all behaviors confirm the general result: The ability of the swarm to adapt improves when robots have fewer communication links. The average number of links per robot reduces when the individual communication range or the robot density decreases. The analysis of the swarm dynamics via mean-field models suggests that our results generalize to other systems based on the voter model. Model predictions are confirmed by results of multiagent simulations and experiments with 50 Kilobot robots. Limiting the communication to a local neighborhood is a cheap decentralized solution to allow robot swarms to adapt to previously unknown information that is locally observed by a minority of the robots

Synthesis and Analysis of Minimalist Control Strategies for Swarm Robotic Systems

The field of swarm robotics studies bio-inspired cooperative control strategies for large groups of relatively simple robots. The robots are limited in their individual capabilities, however, by inducing cooperation amongst them, the limitations can be overcome. Local sensing and interactions within the robotic swarm promote scalable, robust, and flexible behaviours. This thesis focuses on synthesising and analysing minimalist control strategies for swarm robotic systems. Using a computation-free swarming framework, multiple decentralised control strategies are synthesised and analysed. The control strategies enable the robots—equipped with only discrete-valued sensors—to reactively respond to their environment. We present the simplest control solutions to date to four multi-agent problems: finding consensus, gathering on a grid, shepherding, and spatial coverage. The control solutions—obtained by employing an offline evolutionary robotics approach—are tested, either in computer simulation or by physical experiment. They are shown to be—up to a certain extent—scalable, robust against sensor noise, and flexible to the changes in their environment. The investigated gathering problem is proven to be unsolvable using the deterministic framework. The extended framework, using stochastic reactive controllers, is applied to obtain provably correct solutions. Using no run-time memory and only limited sensing make it possible to realise implementations that are arguably free of arithmetic computation. Due to the low computational demands, the control solutions may enable or inspire novel applications, for example, in nanomedicine