25,497 research outputs found
Autonomy: a review and a reappraisal
In the field of artificial life there is no agreement on what defines âautonomyâ. This makes it difficult to measure progress made towards understanding as well as engineering autonomous systems. Here, we review the diversity of approaches and categorize them by introducing a conceptual distinction between behavioral and constitutive autonomy. Differences in the autonomy of artificial and biological agents tend to be marginalized for the former and treated as absolute for the latter. We argue that with this distinction the apparent opposition can be resolved
Information and communication in a networked infosphere: a review of concepts and application in social branding
This paper aims at providing a contribution to the comprehensive review of the impact of information and communication, and their supporting technologies, in the current transformation of human life in the infosphere. The paper also offers an ex- ample of the power of new social approaches to the use of information and commu- nication technologies to foster new working models in organizations by presenting the main outcomes of a research project on social branding. A discussion about some trends of the future impact of new information and communication technologies in the infosphere is also included
Ergonomic Chair Design by Fusing Qualitative and Quantitative Criteria using Interactive Genetic Algorithms
This paper emphasizes the necessity of formally bringing qualitative and
quantitative criteria of ergonomic design together, and provides a novel
complementary design framework with this aim. Within this framework, different
design criteria are viewed as optimization objectives; and design solutions are
iteratively improved through the cooperative efforts of computer and user. The
framework is rooted in multi-objective optimization, genetic algorithms and
interactive user evaluation. Three different algorithms based on the framework
are developed, and tested with an ergonomic chair design problem. The parallel
and multi-objective approaches show promising results in fitness convergence,
design diversity and user satisfaction metrics
Innovation and failure in mechatronics design education
Innovative engineering design always has associated with it the risk of failure, and it is the role of the design engineer to mitigate the possibilities of failure in the final system. Education should however provide a safe space for students to both innovate and to learn about and from failures. However, pressures on course designers and students can result in their adopting a conservative, and risk averse, approach to problem solving. The paper therefore considers the nature of both innovation and failure, and looks at how these might be effectively combined within mechatronics design education
Information and Meaning in Life, Humans and Robots
Information and meaning exist around us and within ourselves, and the same information can correspond to different meanings. This is true for humans and animals, and is becoming true for robots.
We propose here an overview of this subject by using a systemic tool related to meaning generation that has already been published (C. Menant, Entropy 2003).
The Meaning Generator System (MGS) is a system submitted to a constraint that generates a meaningful information when it receives an incident information that has a relation with the constraint. The content of the meaningful information is explicited, and its function is to
trigger an action that will be used to satisfy the constraint of the system.
The MGS has been introduced in the case of basic life submitted to a "stay alive" constraint.
We propose here to see how the usage of the MGS can be extended to more complex living systems, to humans and to robots by introducing new types of constraints, and integrating the MGS into higher level systems.
The application of the MGS to humans is partly based on a scenario relative to the evolution of body self-awareness toward self-consciousness that has already been presented
(C. Menant, Biosemiotics 2003, and TSC 2004).
The application of the MGS to robots is based on the definition of the MGS applied to robots functionality, taking into account the origins of the constraints.
We conclude with a summary of this overview and with themes that can be linked to this systemic approach on meaning generation
An approach to design knowledge capture for the space station
The design of NASA's space station has begun. During the design cycle, and after activation of the space station, the reoccurring need will exist to access not only designs, but also deeper knowledge about the designs, which is only hinted in the design definition. Areas benefiting from this knowledge include training, fault management, and onboard automation. NASA's Artificial Intelligence Office at Johnson Space Center and The MITRE Corporation have conceptualized an approach for capture and storage of design knowledge
Morphological shape generation through user-controlled group metamorphosis
Morphological shape design is interpreted in this paper as a search for new shapes from a particular application domain represented by a set of selected shape instances. This paper proposes a new foundation for morphological shape design and generation. In contrast to existing generative procedures, an approach based on a user-controlled metamorphosis between functionally based shape models is presented. A formulation of the pairwise metamorphosis is proposed with a variety of functions described for the stages of deformation, morphing and offsetting. This formulation is then extended to the metamorphosis between groups of shapes with user-defined, dynamically correlated and weighted feature elements. A practical system was implemented in the form of plugin to Maya and tested by an industrial designer on a group of representative shapes from a particular domain. © 2013 Elsevier Ltd
Implementing feedback in creative systems : a workshop approach
One particular challenge in AI is the computational modelling and simulation of creativity. Feedback and learning from experience are key aspects of the creative process. Here we investigate how we could implement feedback in creative systems using a social model. From the field of creative writing we borrow the concept of a Writers Workshop as a model for learning through feedback. The Writers Workshop encourages examination, discussion and debates of a piece of creative work using a prescribed format of activities. We propose a computational model of the Writers Workshop as a roadmap for incorporation of feedback in artificial creativity systems. We argue that the Writers Workshop setting describes the anatomy of the creative process. We support our claim with a case study that describes how to implement the Writers Workshop model in a computational creativity system. We present this work using patterns other people can follow to implement similar designs in their own systems. We conclude by discussing the broader relevance of this model to other aspects of AI
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