308,705 research outputs found
Complexity-based learning and teaching: a case study in higher education
This paper presents a learning and teaching strategy based on complexity science and explores its impacts on a higher education game design course. The strategy aimed at generating conditions fostering individual and collective learning in educational complex adaptive systems, and led the design of the course through an iterative and adaptive process informed by evidence emerging from course dynamics. The data collected indicate that collaboration was initially challenging for students, but collective learning emerged as the course developed, positively affecting individual and team performance. Even though challenged, students felt highly motivated and enjoyed working on course activities. Their perception of progress and expertise were always high, and the academic performance was on average very good. The strategy fostered collaboration and allowed students and tutors to deal with complex situations requiring adaptation
Collective adaptation through concurrent planning: the case of sustainable urban mobility
In this paper we address the challenges that impede collective adaptation in smart mobility systems by proposing a notion of ensembles. Ensembles enable systems with collective adaptability to be built as emergent aggregations of autonomous and self-adaptive agents. Adaptation in these systems is triggered by a run-time occurrence, which is known as an issue. The novel aspect of our approach is, it allows agents affected by an issue in the context of a smart mobility scenario to adapt collaboratively with minimal impact on their own preferences through an issue resolution process based on concurrent planning algorithms
Devising a Game Theoretic Approach to Enable Smart City Digital Twin Analytics
Despite investments in advancing information and communications technology (ICT)-integrated infrastructure systems toward becoming Smarter Cities, cities often face a large gap between smart sustainable supply and demand. Here, we review the core concepts of ICT-integrated infrastructure systems as they pertain to developing smart and sustainable cities, and describe how a game theoretic-based digital twin of a city can enable more visibility and insight into the successful implementation of such systems. This study is a foundational step toward enabling participation of all city stakeholders (i.e., government, industry, and citizens) in the decision making process and the creation of smart sustainable cities. Engaging city stakeholders in such a manner allows for collective participation in changes, which can enable continuous adaptation toward more sustaining growth and prosperity
On Expressiveness and Behavioural Theory of Attribute-based Communication
Attribute-based communication is an interesting alternative to broadcast and binary communication when providing abstract models for the so called Collective Adaptive Systems which consist of a large number of interacting components that dynamically adjust and combine their behavior to achieve specifc goals. A basic process calculus, named AbC, is introduced whose primary
primitive for interaction is attribute-based communication. An AbC system consists of a set of parallel components each of which is equipped with a set of attributes. Communication takes place in an implicit multicast fashion, and interactions among components are dynamically established by taking into account\connections" as determined by predicates over the attributes
exposed by components. First, the syntax and the semantics of AbC are presented, then expressiveness and effectiveness of the calculus are demonstrated both in terms of the ability to model scenarios featuring collaboration, reconfiguration, and adaptation
and of the possibility of encoding a process calculus for broadcasting channel-based communication and other communication
paradigms. Behavioral equivalences for AbC are introduced for establishing formal relationships between different descriptions
of the same system
Team Learning, Development, and Adaptation
[Excerpt] Our purpose is to explore conceptually these themes centered on team learning, development, and adaptation. We note at the onset that this chapter is not a comprehensive review of the literature. Indeed, solid conceptual and empirical work on these themes are sparse relative to the vast amount of work on team effectiveness more generally, and therefore a thematic set of topics that are ripe for conceptual development and integration. We draw on an ongoing stream of theory development and research in these areas to integrate and sculpt a distinct perspective on team learning, development, and adaptation
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
Adaptation to synchronization in phase-oscillator networks
We introduce an adaptation algorithm by which an ensemble of coupled
oscillators with attractive and repulsive interactions is induced to adopt a
prescribed synchronized state. While the performance of adaptation is
controlled by measuring a macroscopic quantity, which characterizes the
achieved degree of synchronization, adaptive changes are introduced at the
microscopic level of the interaction network, by modifying the configuration of
repulsive interactions. This scheme emulates the distinct levels of selection
and mutation in biological evolution and learning
Towards homeostatic architecture: simulation of the generative process of a termite mound construction
This report sets out to the theme of the generation of a âlivingâ,
homeostatic and self-organizing architectural structure. The main research
question this project addresses is what innovative techniques of design,
construction and materials could prospectively be developed and eventually
applied to create and sustain human-made buildings which are mostly
adaptive, self-controlled and self-functioning, without option to a vast supply
of materials and peripheral services. The hypothesis is that through the
implementation of the biological building behaviour of termites, in terms of
collective construction mechanisms that are based on environmental stimuli,
we could achieve a simulation of the generative process of their adaptive
structures, capable to inform in many ways human construction. The essay
explicates the development of the 3-dimensional, agent-based simulation of
the termite collective construction and analyzes the results, which involve
besides physical modelling of the evolved structures. It finally elucidates the
potential of this emerging and adaptive architectural performance to be
translated to human practice and thus enlighten new ecological engineering
and design methodologies
Cooperative Adaptive Control for Cloud-Based Robotics
This paper studies collaboration through the cloud in the context of
cooperative adaptive control for robot manipulators. We first consider the case
of multiple robots manipulating a common object through synchronous centralized
update laws to identify unknown inertial parameters. Through this development,
we introduce a notion of Collective Sufficient Richness, wherein parameter
convergence can be enabled through teamwork in the group. The introduction of
this property and the analysis of stable adaptive controllers that benefit from
it constitute the main new contributions of this work. Building on this
original example, we then consider decentralized update laws, time-varying
network topologies, and the influence of communication delays on this process.
Perhaps surprisingly, these nonidealized networked conditions inherit the same
benefits of convergence being determined through collective effects for the
group. Simple simulations of a planar manipulator identifying an unknown load
are provided to illustrate the central idea and benefits of Collective
Sufficient Richness.Comment: ICRA 201
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