Publications by authors named "Seth Bullock"

Novelty detection allows robots to recognise unexpected data in their sensory field and can thus be utilised in applications such as reconnaissance, surveillance, self-monitoring, etc. We assess the suitability of Grow When Required Neural Networks (GWRNNs) for detecting novel features in a robot's visual input in the context of randomised physics-based simulation environments. We compare, for the first time, several GWRNN architectures, including new Plastic architectures in which the number of activated input connections for individual neurons is adjusted dynamically as the robot senses a varying number of salient environmental features.

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Objectives: Attractiveness judgements have been shown to affect interpersonal relationships. The present study explored the relationships between perceived attractiveness, perceived sexual health status, condom use intentions and condom use resistance in women.

Setting: The study data were collected using an online questionnaire.

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In swarm robotics, a design pattern provides high-level guidelines for the implementation of a particular robot behaviour and describes its impact on swarm performance. In this paper, we explore information exchange design patterns for robot swarm foraging. First, a method for the specification of design patterns for robot swarms is proposed that builds on previous work in this field and emphasises modular behaviour design, as well as information-centric micro-macro link analysis.

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The study of complex networks, and in particular of social networks, has mostly concentrated on relational networks, abstracting the distance between nodes. Spatial networks are, however, extremely relevant in our daily lives, and a large body of research exists to show that the distances between nodes greatly influence the cost and probability of establishing and maintaining a link. A random geometric graph (RGG) is the main type of synthetic network model used to mimic the statistical properties and behavior of many social networks.

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Social learning, defined as the imitation of behaviors performed by others, is recognized as a distinctive characteristic in humans and several other animal species. Previous work has claimed that the evolutionary fixation of social learning requires decision-making cognitive abilities that result in transmission bias (e.g.

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Background: Sexually transmitted infections (STIs) are ongoing concerns. The best method for preventing the transmission of these infections is the correct and consistent use of condoms. Few studies have explored the use of games in interventions for increasing condom use by challenging the false sense of security associated with judging the presence of an STI based on attractiveness.

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Objectives: Judgements of attractiveness have been shown to influence the character of social interactions. The present study sought to better understand the relationship between perceived attractiveness, perceived sexual health status and condom use intentions in a heterosexual male population.

Setting: The study employed an electronic questionnaire to collect all data, during face-to-face sessions.

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Rayleigh-Bénard convection is a canonical example of spontaneous pattern formation in a nonequilibrium system. It has been the subject of considerable theoretical and experimental study, primarily for systems with constant (temperature or heat flux) boundary conditions. In this investigation, we have explored the behavior of a convecting fluid system with negative feedback boundary conditions.

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We introduce a distinction between algorithm performance and algorithm competence and argue that bio-inspired computing should characterize the former rather than the latter. To exemplify this, we explore and extend a bio-inspired algorithm for collective construction influenced by paper wasp behavior. Despite its being provably general in its competence, we demonstrate limitations on the algorithm's performance.

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Article Synopsis
  • The 'Perfect Storm' metaphor highlights how various events can combine to create surprising impacts in social-ecological systems, emphasizing the need to understand their evolution.
  • An effective research strategy involves creating long-term records by integrating various data sources and developing advanced modeling techniques to analyze complex behaviors in these systems.
  • It's crucial to improve the communication of complex systems, risk, and uncertainty to ensure informed decision-making by the public and policy-makers.
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A game-theoretic model of handicap signalling over a pair of signalling channels is introduced in order to determine when one channel has an evolutionary advantage over the other. The stability conditions for honest handicap signalling are presented for a single channel and are shown to conform with the results of prior handicap signalling models. Evolutionary simulations are then used to show that, for a two-channel system in which honest signalling is possible on both channels, the channel featuring larger advertisements at equilibrium is favoured by evolution.

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The structure of many biological, social and technological systems can usefully be described in terms of complex networks. Although often portrayed as fixed in time, such networks are inherently dynamic, as the edges that join nodes are cut and rewired, and nodes themselves update their states. Understanding the structure of these networks requires us to understand the dynamic processes that create, maintain and modify them.

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In this paper we demonstrate that signal propagation across a laminar sheet of recurrent neurons is maximised when two conditions are met. First, neurons must be in the so-called centre crossing configuration. Second, the network's topology and weights must be such that the network comprises strongly coupled nodes, yet lies within the weakly coupled regime.

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A plant's morphology is both strongly influenced by local light availability and, simultaneously, strongly influences this local light availability. This reciprocal relationship is complex, but lies at the heart of understanding plant growth and competition. Here, we develop a sub-individual-based simulation model, cast at the level of interacting plant components.

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Evolutionary activity statistics and their visualization are introduced, and their motivation is explained. Examples of their use are described, and their strengths and limitations are discussed. References to more extensive or general accounts of these techniques are provided.

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Visualization has an increasingly important role to play in scientific research. Moreover, visualization has a special role to play within artificial life as a result of the informal status of its key explananda: life and complexity. Both are poorly defined but apparently identifiable via raw inspection.

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The literature on innovation suggests that projects are successful when rigorous project management is mixed judiciously with 'organic' development. This paper argues that organic growth can play a substantial role in the implementation of electronic services in healthcare settings. Evidence for organic growth is presented, based on a study of email use.

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In previous models of the building behaviour of termites, physical and logistic constraints that limit the movement of termites and pheromones have been neglected. Here, we present an individual-based model of termite construction that includes idealized constraints on the diffusion of pheromones, the movement of termites, and the integrity of the architecture that they construct. The model allows us to explore the extent to which the results of previous idealized models (typically realised in one or two dimensions via a set of coupled partial differential equations) generalize to a physical, 3-D environment.

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While standard evolutionary algorithms employ a static, absolute fitness metric, coevolutionary algorithms assess individuals by their performance relative to populations of opponents that are themselves evolving. Although this arrangement offers the possibility of avoiding long-standing difficulties such as premature convergence, it suffers from its own unique problems, cycling, over-focusing and disengagement. Here, we introduce a novel technique for dealing with the third and least explored of these problems.

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Many artificial life researchers stress the interdisciplinary character of the field. Against such a backdrop, this report reviews and discusses artificial life, as it is depicted in, and as it interfaces with, adjacent disciplines (in particular, philosophy, biology, and linguistics), and in the light of a specific historical example of interdisciplinary research (namely cybernetics) with which artificial life shares many features. This report grew out of a workshop held at the Sixth European Conference on Artificial Life in Prague and features individual contributions from the workshop's eight speakers, plus a section designed to reflect the debates that took place during the workshop's discussion sessions.

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