Multitask Evolution with Cartesian Genetic Programming

We introduce a genetic programming method for solving multiple Boolean circuit synthesis tasks simultaneously. This allows us to solve a set of elementary logic functions twice as easily as with a direct, single-task approach.Comment: 2 page

Collective decision making in distributed systems inspired by honeybees behaviour

We propose a design methodology to provide cognitive capabilities to large-scale artificial distributed systems. The behaviour of such systems is the result of non-linear interactions of the individuals with each other and with the environment, and the resulting system behaviour is in general difficult to predict. The proposed methodology is based on the concept of cognitive design patterns, that is, reusable solutions to tackle problems requiring cognitive abilities (e.g., decision-making, attention, categorisation). Cognitive design patterns aim to support the engineering of distributed systems through guidelines and theoretical models that link the individual control rules of the agents to the desired global behaviour. In this paper, we propose a cognitive design pattern for collective decision-making inspired by the nest-site selection behaviour of honeybee swarms. We describe and analyse the theoretical models, and distill a set of guidelines for the implementation of collective decisions in distributed multi-agent systems. We demonstrate the validity of the cognitive design pattern in a case study involving spatial factors: the collective selection of the shortest path between two target areas. We analyse the dynamics of the multi-agent system and we show a very good adherence with the predictions of the macroscopic model. Future refinements of the cognitive design pattern will allow its usage in different application domains

L'opera di Andrija Maurović, padre del fumetto croato

Sul ‘padre del fumetto croato’ rimane ancora molto da scoprire. La storia del fumetto in Croazia e nell’ex Jugoslavia ha inizio con il nome di Maurović, sicuramente il più importante fumettista croato del XX secolo. Il suo primo fumetto, Vjerenica mača, fu pubblicato nel 1935. Maurović visse tutta la complessità del secolo breve e il destino dei suoi fumetti seguì i grandi sommovimenti di quell’epoca: prima, durante e dopo la Seconda guerra mondiale. Come artista, dovette fare i conti con diversi sistemi e regimi. Partecipò alla lotta di liberazione partigiana, rimanendo fedele a se stesso e alle proprie idee fino alla fine dei suoi giorni. Sulla sua vita ‘fuori dagli schemi’, con alti e bassi, circolano numerose leggende. Oltre al fumetto, si dedicò alle caricature, ai poster, alle pubblicità ed alle illustrazioni, iniziando e concludendo la propria parabola artistica con opere a tema erotico

Evolutionary swarm robotics: a theoretical and methodological itinerary from individual neuro-controllers to collective behaviours

In the last decade, swarm robotics gathered much attention in the research community. By drawing inspiration from social insects and other self-organizing systems, it focuses on large robot groups featuring distributed control, adaptation, high robustness, and flexibility. Various reasons lay behind this interest in similar multi-robot systems. Above all, inspiration comes from the observation of social activities, which are based on concepts like division of labor, cooperation, and communication. If societies are organized in such a way in order to be more efficient, then robotic groups also could benefit from similar paradigms

A quantitative micro-macro link for collective decisions: the shortest path discovery/selection example

In this paper, we study how to obtain a quantitative correspondence between the dynamics of the microscopic implementation of a robot swarm and the dynamics of a macroscopic model of nest-site selection in honeybees. We do so by considering a collec- tive decision-making case study: the shortest path discovery/selection problem. In this case study, obtaining a quantitative correspondence between the microscopic and macroscopic dynamics-the so-called micro-macro link problem-is particularly challenging because the macroscopic model does not take into account the spatial factors inherent to the path discovery/selection problem. We frame this study in the context of a general engineering methodology that prescribes the inclusion of available theoretical knowledge about target macroscopic models into design patterns for the microscopic implementation. The attain- ment of the micro-macro link presented in this paper represents a necessary step towards the formalisation of a design pattern for collective decision making in distributed systems

A survey on metaheuristics for stochastic combinatorial optimization

Metaheuristics are general algorithmic frameworks, often nature-inspired, designed to solve complex optimization problems, and they are a growing research area since a few decades. In recent years, metaheuristics are emerging as successful alternatives to more classical approaches also for solving optimization problems that include in their mathematical formulation uncertain, stochastic, and dynamic information. In this paper metaheuristics such as Ant Colony Optimization, Evolutionary Computation, Simulated Annealing, Tabu Search and others are introduced, and their applications to the class of Stochastic Combinatorial Optimization Problems (SCOPs) is thoroughly reviewed. Issues common to all metaheuristics, open problems, and possible directions of research are proposed and discussed. In this survey, the reader familiar to metaheuristics finds also pointers to classical algorithmic approaches to optimization under uncertainty, and useful informations to start working on this problem domain, while the reader new to metaheuristics should find a good tutorial in those metaheuristics that are currently being applied to optimization under uncertainty, and motivations for interest in this fiel

Autonomous Construction with Compliant Building Material

In this paper, we develop an autonomous construction system in which a self-contained ground robot builds a protective barrier by means of compliant pockets (i.e., filled bags). We present a stochastic control algorithm based on two biological mechanisms (stigmergy and templates) that takes advantage of compliant pockets for autonomous construction. The control algorithm guides the robot to build the structure without relying on any external motion capture system or external computer. We propose a statistical model to represent the structures built with the compliant pockets, and we provide a set of criteria for assessing the performance of the proposed system. To demonstrate the feasibility of the proposed system, real-robot experiments were carried out. In each experiment, the robot successfully built the structure. The results show the viability of the proposed autonomous construction system

Self-Assembly in Physical Autonomous Robots: the Evolutionary Robotics Approach

info:eu-repo/semantics/publishe