Andreagiovanni Reina

The University of Sheffield | Sheffield · Department of Computer Science (Faculty of Engineering)

Full text available at: http://www.ifaamas.org/Proceedings/aamas2014/aamas/p1421.pdf

We introduce the concept of cognitive design pattern to provide a design methodology for distributed multi-agent systems. A cognitive design pattern is a reusable solution to tackle problems requiring cognitive abilities (e.g., decision-making, attention, categorisation). It provides theoretical models and design guidelines to define the individual...

Abstract We introduce zePPeLIN, a distributed system designed to address the challenges of path planning in large, cluttered, dynamic environments. The objective is to define a sequence of instructions to precisely move a ground object (e.g., a mobile robot) from an initial to a final configuration in an environment. zePPeLIN is based on a set of wire...

Robot swarms are generally considered to be composed of cooperative agents that, despite their limited individual capabilities, can perform difficult tasks by working together. However, in open swarms, where different robots can be added to the swarm by different parties with potentially competing interests, cooperation is but one of many strategie...

Research with swarm robotics systems can be complicated, time-consuming, and often expensive in terms of space and resources. The situation is even worse for studies involving multiple, possibly heterogeneous robot swarms. Augmented reality can provide an interesting solution to these problems, as demonstrated by the ARK system (Augmented Reality f...

Strongly opinionated minorities can have a dramatic impact on the opinion dynamics of a large population. Two factions of inflexible minorities, polarised into two competing opinions, could lead the entire population to persistent indecision. Equivalently, populations can remain undecided when individuals sporadically change their opinion based on...

We investigate how reliable movement can emerge in aggregates of highly error-prone individuals. The individuals—robotic modules—move stochastically using vibration motors. By coupling them via elastic links, soft-bodied aggregates can be created. We present distributed algorithms that enable the aggregates to move and deform reliably. The concept...

A swarm is a group of agents with local knowledge of the environment, that collaborate, coordinating their actions in order to perform a task. In this study, I address the best-of-n problem, where the objective of the swarm is that of reaching an agreement on the best among n options, each having an associated quality. I focus on the collective dec...

It is usually assumed that information cascades are most likely to occur when an early but incorrect opinion spreads through the group. Here, we analyse models of confidence-sharing in groups and reveal the opposite result: simple but plausible models of naive-Bayesian decision-making exhibit information cascades when group decisions are synchronou...

Collective intelligence and autonomy of robot swarms can be improved by enabling the individual robots to become aware they are the constituent units of a larger whole and what is their role. In this study, we present an algorithm to enable positional self-awareness in a swarm of minimalistic error-prone robots which can only locally broadcast mess...

Strongly opinionated minorities can have a dramatic impact on the opinion dynamics of a large population. Two factions of inflexible minorities, polarised into two competing opinions, could lead the entire population to persistent indecision. Equivalently, populations can remain undecided when individuals sporadically change their opinion based on...

We study how robot swarms can achieve a consensus on the best among a set of n possible options available in the environment. While the robots rely on local communication with one another, follow simple rules, and make estimates of the option’s qualities subject to measurement errors, the swarm as a whole is able to make accurate collective decisio...

We aim to design algorithms that allow robot swarms to solve the best-of-n problem using as little resources as possible. Our minimalistic approach aims to create solutions suitable for simple robots with fewer memory and computational requirements than the state of the art algorithms require. While the long term goal is to implement decentralised...

Self-organized aggregation is a well studied behavior in swarm robotics as it is the pre-condition for the development of more advanced group-level responses. In this paper, we investigate the design of decentralized algorithms for a swarm of heterogeneous robots that self-aggregate over distinct target sites. A previous study has shown that includ...

Most of our experiences, as well as our intuition, are usually built on a linear understanding of systems and processes. Complex systems in general, and more specifically swarm robotics in this context, leverage non-linear effects to self-organize and to ensure that ‘more is different’. In previous work, the non-linear and therefore counter-intuiti...

We present a novel control scheme for robot swarms that exploits the computation layer of a blockchain to coordinate the actions of individual robots in real-time. To accomplish this, we deploy a blockchain smart contract that acts as a “decentralized supervisor” during a swarm foraging task. Our results show that using blockchain-based global coor...

Optimality analysis of value-based decisions in binary and multi-alternative choice settings predicts that reaction times should be sensitive only to differences in stimulus magnitudes, but not to overall absolute stimulus magnitude. Yet experimental work in the binary case has shown magnitude sensitive reaction times, and theory shows that this ca...

Self-organised aggregation is one of the basic collective behaviours studied in swarm robotics. In this paper, we investigate an aggregation problem occurring on two different sites. Previous studies have shown that a minority of robots, informed about the site on which they have to aggregate, can control the final distribution of the entire robot...

In this study, we investigate the emergence of naming conventions within a swarm of robots that collectively forage, that is, collect resources from multiple sources in the environment. While foraging, the swarm explores the environment and makes a collective decision on how to exploit the available resources, either by selecting a single source or...

Self-organised aggregation is a well studied behaviour in swarm robotics as it is the pre-condition for the development of more advanced group-level responses. In this paper, we investigate the design of decentralised algorithms for a swarm of heterogeneous robots that self-aggregate over distinct target sites. A previous study has shown that inclu...

It is usually assumed that information cascades are most likely to occur when an early but incorrect opinion spreads through the group. Here we analyse models of confidence-sharing in groups and reveal the opposite result: simple but plausible models of naïve Bayesian decision-making exhibit information cascades when group decisions are synchronous...

Node counting on a graph is subject to some fundamental theoretical limitations, yet a solution to such problems is necessary in many applications of graph theory to real-world systems, such as collective robotics and distributed sensor networks. Thus several stochastic and naïve deterministic algorithms for distributed graph size estimation or cal...

Magnitude-sensitivity refers to the result that performance in decision-making, across domains and organisms, is affected by the total value of the possible alternatives. This simple result offers a window into fundamental issues in decision-making and has led to a reconsideration of ecological decision-making, prominent computational models of dec...

Recent work has derived the optimal policy for two-alternative value-based decisions, in which decision-makers compare the subjective expected reward of two alternatives. Under specific task assumptions — such as linear utility, linear cost of time and constant processing noise — the optimal policy is implemented by a diffusion process in which par...

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. Th...

A scalable system has increasing performance with increasing system size. Coordination among units can introduce overheads with an impact on system performance. The coordination costs can lead to sublinear improvement or even diminishing performance with increasing system size. However, there are also systems that implement efficient coordination a...

Optimality analysis of value-based decisions in binary and multi-alternative choice settings predicts that reaction times should be sensitive only to differences in stimulus magnitudes, but not to overall absolute stimulus magnitude. Yet experimental work in the binary case has shown magnitude sensitive reaction times, and theory shows that this ca...

Scalability is a key feature of swarm robotics. Hence, measuring performance depending on swarm size is important to check the validity of the design. Performance diagrams have generic qualities across many different application scenarios. We summarize these findings and condense them in a practical performance analysis guide for swarm robotics. We...

Efficient engineered systems require scalability. A scalable system has increasing performance with increasing system size. In an ideal case, the increase in performance (e.g., speedup) corresponds to the number of units that are added to the system. However, if multiple units work on the same task, then coordination among these units is required....

Social insect colonies use negative as well as positive feedback signals to regulate foraging behaviour. In ants and bees individual foragers have been observed to use negative pheromones or mechano-auditory signals to indicate that forage sources are not ideal, for example being unrewarded, crowded, or dangerous. Here we propose an alternative fun...

How groups of cooperative foragers can achieve efficient and robust collective foraging is of interest both to biologists studying social insects and engineers designing swarm robotics systems. Of particular interest are distance-quality trade-offs and swarm-size-dependent foraging strategies. Here, we present a collective foraging system based on...

Modelling plays a key role in explaining data in psychology and neuroscience and helps elucidate neural computations. Recent observations of magnitude-sensitivity (i.e. sensitivity to overall magnitudes and magnitude differences) in both humans engaged in perceptual decision making and monkeys engaged in value-based decisions have shown that new as...

Node counting on a graph is subject to some fundamental theoretical limitations, yet a solution to such problems is necessary in many applications of graph theory to real-world systems, such as collective robotics and distributed sensor networks. Thus several stochastic and na{\"i}ve deterministic algorithms for distributed graph size estimation or...

Decentralised systems composed of a large number of locally interacting agents often rely on coherent behaviour to execute coordinated tasks. Agents cooperate to reach a coherent collective behaviour by aligning their individual behaviour to the one of their neighbours. However, system noise, determined by factors such as individual exploration or...

Will the Third World War be fought by robots? This short film is a light-hearted comedy that aims to trigger an interesting discussion and reflexion on the terrifying killer-robot stories that increasingly fill us with dread when we read the news headlines. The fictional scenario takes inspiration from current scientific research and describes a fu...

We investigate the emergence of language convention within a swarm of robots foraging in an open environment from two identical resources. While foraging, the swarm needs to explore and decide which resource to exploit, moving through complex transitory dynamics towards different possible equilibria, such as, selection of a single resource or sprea...

Collective behaviour is of fundamental importance in the life sciences, where it appears at levels of biological complexity from single cells to superorganisms, in demography and the social sciences, where it describes the behaviour of populations, and in the physical and engineering sciences, where it describes physical phenomena and can be used t...

We theoretically study decision-making behaviour in a model-based analysis related to binary choices with pulsed stimuli. Assuming a strong coupling between external stimulus and its internal representation, we argue that the frequency of external periodic stimuli represents an important degree of freedom in decision-making which may modulate behav...

Decision making is a complex task, and its underlying mechanisms that regulate behavior, such as the implementation of the coupling between physiological states and neural networks, are hard to decipher. To gain more insight into neural computations underlying ongoing binary decision-making tasks, we consider a neural circuit that guides the feedin...

Large swarms of simple autonomous robots can be employed to find objects clustered at random locations, and transport them to a central depot. This solution offers system parallelisation through concurrent environment exploration and object collection by several robots, but it also introduces the challenge of robot coordination. Inspired by ants’ f...

The Kilobot is a popular platform for swarm robotics research due to its low cost and ease of manufacturing. Despite this, the effort to bootstrap the design of new behaviours and the time necessary to develop and debug new behaviours is considerable. To make this process less burdensome, high-performing and flexible simulation tools are important....

Decision-making is a complex task and requires adaptive mechanisms that facilitate efficient behaviour. Here, we consider a neural circuit that guides the behaviour of an animal in ongoing binary choice tasks. We adopt an inhibition motif from neural network theory and propose a dynamical system characterized by nonlinear feedback, which links mech...

The Kilobot is a popular platform for swarm robotics research due to its low cost and ease of manufacturing. Despite this, the effort to bootstrap the design of new behaviours and the time necessary to develop and debug new behaviours is considerable. To make this process less burdensome, high-performing and flexible simulation tools are important....

Value-sensitive decision-making is an essential task for organisms at all levels of biological complexity and consists of choosing options among a set of alternatives and being rewarded according to the quality value of the chosen option. Provided that the chosen option has an above-threshold quality value, value-sensitive decisions are particularl...

Through theoretical analysis, we show how a superorganism may react to stimulus variations according to psychophysical laws observed in humans and other animals. We investigate an empirically-motivated honeybee house-hunting model, which describes a value-sensitive decision process over potential nest-sites, at the level of the colony. In this stud...

Collective decision-making is the subfield of collective behaviour concerned with how groups reach decisions. Almost all aspects of behaviour can be considered in a decision-making context, but here we focus primarily on how groups should optimally reach consensus, what criteria decision-makers should optimise, and how individuals and groups should...

Through this study, we introduce the idea of applying scheduling techniques to allocate spatial resources that are shared among multiple robots moving in a static environment and having temporal constraints on the arrival time to destinations. To illustrate this idea, we present an exemplified algorithm that plans and assigns a motion path to each...

Working with large swarms of robots has challenges in calibration, sensing, tracking, and control due to the associated scalability and time requirements. Kilobots solve this through their ease of maintenance and programming, and are widely used in several research laboratories worldwide where their low cost enables large-scale swarms studies. Howe...

The ability of a honeybee swarm to select the best nest site plays a fundamental role in determining the future colony's fitness. To date, the nest-site selection process has mostly been modelled and theoretically analysed for the case of binary decisions. However, when the number of alternative nests is larger than two, the decision process dynami...

Value-sensitive decision-making is an essential task for organisms at all levels of biological complexity and consists of choosing options among a set of alternatives and being rewarded according to the quality value of the chosen option. Provided that the chosen option has an above-threshold quality value, valuesensitive decisions are particularly...

Imagine you are in ice-cream shop and you are faced with the decision of what ice-cream to order. Will you choose your favourite taste (i.e. vanilla) or will you explore different options discovering a new taste that may turn out to become your new favourite (i.e. pistachio)? This example illustrates the dilemma between exploiting high-rewarded/wel...

Consensus dynamics in decentralised multiagent systems are subject to intense studies, and several different models have been proposed and analysed. Among these, the naming game stands out for its simplicity and applicability to a wide range of phenomena and applications, from semiotics to engineering. Despite the wide range of studies available, t...

The engineering of large-scale decentralised systems requires sound methodologies to guarantee the attainment of the desired macroscopic system-level behaviour given the microscopic individual-level implementation. While a general-purpose methodology is currently out of reach, specific solutions can be given to broad classes of problems by means of...

We present a novel technology that allows real robots to perceive an augmented reality environment through virtual sensors. Virtual sensors are a useful and desirable technology for research activities because they allow researchers to quickly and efficiently perform experiments that would otherwise be more expensive, or even impossible. In particu...

We present two empirical studies on the design of control software for robot swarms. In Study A, Vanilla and EvoStick, two previously published automatic design methods, are compared with human designers. The comparison is performed on five swarm robotics tasks that are different from those on which Vanilla and EvoStick have been previously tested....

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 collective decision making case study: the shortest path discovery/selection problem. In this case study, o...

We present an experiment in automatic design of robot swarms. For the first time in the swarm robotics literature, we perform an objective comparison of multiple design methods: we compare swarms de-signed by two automatic methods—AutoMoDe-Vanilla and EvoStick— with swarms manually designed by human experts. AutoMoDe-Vanilla and EvoStick have been...

We present an experiment in automatic design of robot swarms. For the first time in the swarm robotics literature, we perform an objective comparison of multiple design methods: we compare swarms designed by two automatic methods—vanilla and EvoStick—with swarms manually designed by human experts. vanilla and EvoStick have been previously published...

Deployment of WSNs is an important issue that requires careful consideration, as it can make the difference between an efficient and an unproductive system. The introduction of node mobility provides a wealth of potential solutions to the deployment problem, which can lead to higher robustness, flexibility and adaptivity. When provided with mobilit...

We study how a swarm of ground-based robots, with no knowledge of the environment, can be guided to destination by a group of aerial robots. We show that if the ground-based robots maintain group cohesion, it is possible to create a closed-loop among aerial robots and ground-based robots that results in robust navigation even in presence of high se...

We study a distributed approach to path planning. We focus on holonomic kinematic motion in cluttered 2D areas. The problem consists in defining the precise sequence of roto-translations of a rigid object of arbitrary shape that has to be transported from an initial to a final location through a large, cluttered environment. Our planning system is...

We study a distributed approach to the path planning problem. We focus on holonomic kinematic motion in a plane with static ob-stacles. The problem consists in planning the path of a rigid object of arbitrary shape that has to be transported from an initial to a final location through a constrained path. The planner observes the envi-ronment from a...