Embodied Evolution in Collective Robotics: A Review

This paper provides an overview of evolutionary robotics techniques applied to on-line distributed evolution for robot collectives -- namely, embodied evolution. It provides a definition of embodied evolution as well as a thorough description of the underlying concepts and mechanisms. The paper also presents a comprehensive summary of research published in the field since its inception (1999-2017), providing various perspectives to identify the major trends. In particular, we identify a shift from considering embodied evolution as a parallel search method within small robot collectives (fewer than 10 robots) to embodied evolution as an on-line distributed learning method for designing collective behaviours in swarm-like collectives. The paper concludes with a discussion of applications and open questions, providing a milestone for past and an inspiration for future research.Comment: 23 pages, 1 figure, 1 tabl

Evolutionary games on graphs

Game theory is one of the key paradigms behind many scientific disciplines from biology to behavioral sciences to economics. In its evolutionary form and especially when the interacting agents are linked in a specific social network the underlying solution concepts and methods are very similar to those applied in non-equilibrium statistical physics. This review gives a tutorial-type overview of the field for physicists. The first three sections introduce the necessary background in classical and evolutionary game theory from the basic definitions to the most important results. The fourth section surveys the topological complications implied by non-mean-field-type social network structures in general. The last three sections discuss in detail the dynamic behavior of three prominent classes of models: the Prisoner's Dilemma, the Rock-Scissors-Paper game, and Competing Associations. The major theme of the review is in what sense and how the graph structure of interactions can modify and enrich the picture of long term behavioral patterns emerging in evolutionary games.Comment: Review, final version, 133 pages, 65 figure

Behavioral types in programming languages

A recent trend in programming language research is to use behav- ioral type theory to ensure various correctness properties of large- scale, communication-intensive systems. Behavioral types encompass concepts such as interfaces, communication protocols, contracts, and choreography. The successful application of behavioral types requires a solid understanding of several practical aspects, from their represen- tation in a concrete programming language, to their integration with other programming constructs such as methods and functions, to de- sign and monitoring methodologies that take behaviors into account. This survey provides an overview of the state of the art of these aspects, which we summarize as the pragmatics of behavioral types

A Survey on Thread-Level Speculation Techniques

Producción CientíficaThread-Level Speculation (TLS) is a promising technique that allows the parallel execution of sequential code without relying on a prior, compile-time-dependence analysis. In this work, we introduce the technique, present a taxonomy of TLS solutions, and summarize and put into perspective the most relevant advances in this field.MICINN (Spain) and ERDF program of the European Union: HomProg-HetSys project (TIN2014-58876-P), CAPAP-H5 network (TIN2014-53522-REDT), and COST Program Action IC1305: Network for Sustainable Ultrascale Computing (NESUS)

Verificação e sintese de sistemas hibridos

Orientador: Arnaldo Vieira MouraDissertação (mestrado) - Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: Sistemas distribuídos híbridos advêm da interconexão de sistemas de dinâmica contínua com sistemas de dinâmica discreta. A noção de autômatos híbridos oferece meios para a construção de especificações formais para tais sistemas. Autômatos híbridos são autômatos finitos, onde cada estado descreve um perfil dinâmico do sistema e cujas transições entre estados provocam alterações nestes perfis dinâmicos. Neste trabalho, alguns sistemas híbridos reais são modelados através de autômatos híbridos. Em seguida, os modelos construídos são verificados, usando-se das facilidades de uma ferramenta computacional. Além disso, alguns parâmetros importantes, que afetam o comportamento operacional dos modelos, têm seus valores sintetizados. Os sistemas alvo desse trabalho são segmentos de via de uma malha metroviária e um sistema de gerenciamento de tráfego aéreo. As verificações foram sempre conduzidas de maneira a garantir uma operação segura dos sistemas estudados. As sínteses realizadas contribuíram para determinar valores mais justos para os parâmetros operacionais enfocados, mantendo a segurança na operação dos sistemas alvo.Abstract: Distributed hybrid systems result from the interplay of continuous and discrete dynamics systems. The notion of hybrid automata offers a way to formally specify such systems. A hybrid automaton is a finite state automaton, where each state is extended to contain a description for a system dynamie profile. Transitions between states model a change in the system dynamies. In this work, some real hybrid systems are modeled using the formalism of hybrid automata. Next, the models constructed are verified, using the support of a computational tool. Moreover, values are synthesized for some important parameters that affect the system operational behavior. The target systems treated here are segments of a subway mesh and an air traffice control system. The verification sessions aimed at certifying that the system operates safely. Results from the synthesis contributed to obtain tighter values for operational system parameters, while still guaranteeing its safe operation.MestradoMestre em Ciência da Computaçã

A survey of swarm intelligence for dynamic optimization: algorithms and applications

Swarm intelligence (SI) algorithms, including ant colony optimization, particle swarm optimization, bee-inspired algorithms, bacterial foraging optimization, firefly algorithms, fish swarm optimization and many more, have been proven to be good methods to address difficult optimization problems under stationary environments. Most SI algorithms have been developed to address stationary optimization problems and hence, they can converge on the (near-) optimum solution efficiently. However, many real-world problems have a dynamic environment that changes over time. For such dynamic optimization problems (DOPs), it is difficult for a conventional SI algorithm to track the changing optimum once the algorithm has converged on a solution. In the last two decades, there has been a growing interest of addressing DOPs using SI algorithms due to their adaptation capabilities. This paper presents a broad review on SI dynamic optimization (SIDO) focused on several classes of problems, such as discrete, continuous, constrained, multi-objective and classification problems, and real-world applications. In addition, this paper focuses on the enhancement strategies integrated in SI algorithms to address dynamic changes, the performance measurements and benchmark generators used in SIDO. Finally, some considerations about future directions in the subject are given