Tagged behavior based systems: integrating cognition with embodied activity

Focuses on tagged behavior-based systems-supporting a large subset of classical AI architectures while allowing object representations to remain distributed across multiple sensory and representational modalities.     

A framework for embodied evolution with pre-evaluation applied to a biped robot

Embodied evolution (EE) is a methodology in evolutionary robotics in which, without simulations on a host computer, real robots evolve on the basis of their interactions with the actual environment. However, when adopting EE, we had to accept robot behavior with a low fitness, especially in the early generations. This article introduces pre-evaluation into the EE framework for a biped robot in order to restrain the behavior of a robot of which the fitness is estimated to be low, especially falling down onto the ground. We provide a comparative discussion on the conventional simulate-and-transfer method, the original EE method, and the proposed one in terms of calculation time, cost of fitness evaluation, and cost of simulation or modeling based on the evaluation experiments. We believe that the EE framework with pre-evaluation is applicable to a wide variety of optimization tasks in which the cost or the risk of fitness evaluation is not negligible.     

Distributed cognition as a theoretical framework for information visualization

Even though information visualization (InfoVis) research has matured in recent years, it is generally acknowledged that the field still lacks supporting, encompassing theories. In this paper, we argue that the distributed cognition framework can be used to substantiate the theoretical foundation of InfoVis. We highlight fundamental assumptions and theoretical constructs of the distributed cognition approach, based on the cognitive science literature and a real life scenario. We then discuss how the distributed cognition framework can have an impact on the research directions and methodologies we take as InfoVis researchers. Our contributions are as follows. First, we highlight the view that cognition is more an emergent property of interaction than a property of the human mind. Second, we argue that a reductionist approach to study the abstract properties of isolated human minds may not be useful in informing InfoVis design. Finally we propose to make cognition an explicit research agenda, and discuss the implications on how we perform evaluation and theory building.     

Rhythmic synchrony and mediated interaction: towards a framework of rhythm in embodied interaction

Our everyday interactions increasingly involve both embodied face-to-face communication and various forms of mediated and distributed communication such as email, skype, and facebook. In daily face-to-face communications, we are connected in rhythm and synchrony at multiple levels ranging from the moment-by-moment continuity of timed syllables to emergent body and vocal rhythms of pragmatic sense-making. Our human capacity to synchronize with each other may be essential for our survival as social beings. Moving our bodies and voices together in time embodies a potent pragmatic purpose that of being together. In this synchrony of self with other, witnessing and being present become part of each other. There is growing research into how rhythm and synchrony operate in embodied face-to-face interaction and this provides parameters for investigating the relations and differences in how we connect and are socially present in the embodied and distributed settings, and understanding the effect of one setting upon the other. This paper explores the arena of research into rhythm in human interaction, musical and linguistic, with a focus on the movements of body and voice. It draws together salient issues and ideas that would form the basis for a framework of rhythm in embodied interaction.     

Mindful: A framework for Meta-INDuctive neuro-FUzzy Learning

Common inductive learning strategies offer tools for knowledge acquisition, but possess some inherent limitations due to the use of fixed bias during the learning process. To overcome the limitations of such base-learning approaches, a research trend explores the potentialities of meta-learning, which is oriented to the development of mechanisms based on a dynamical search of bias. This may lead to an improvement of the base-learner performance on specific learning tasks, by profiting of the accumulated past experience. In this paper, we present a meta-learning framework called Mindful (Meta INDuctive neuro-FUzzy Learning) which is founded on the integration of connectionist paradigms and fuzzy knowledge management. Due to its peculiar organisation, Mindful can be exploited on different levels of application, being able to accumulate learning experience in cross-task contexts. This specific knowledge is gathered during the meta-learning activity and it is exploited to suggest parametrisation for future base-learning tasks. The evaluation of the Mindful system is detailed through an ensemble of experimental sessions involving both synthetic domains and real-world data.     

Learning handwriting by evolution: a conceptual framework for performance evaluation and tuning

In this paper we propose a method for evaluating the performance of an evolutionary learning system aimed at producing the optimal set of prototypes to be used by a handwriting recognition system. The trade-off between generalization and specialization embedded into any learning process is managed by iteratively estimating both consistency and completeness of the prototypes, and by using such an estimate for tuning the learning parameters in order to achieve the best performance with the smallest set of prototypes. Such estimation is based on a characterization of the behavior of the learning system, and is accomplished by means of three performance indices. Both the characterization and the indices do not depend on either the system implementation or the application, and therefore allow for a truly black-box approach to the performance evaluation of any evolutionary learning system.     

Creative cognition: A multidisciplinary and integrative framework of creative thinking

Extant research provides vast information on antecedents to creativity. However, creative thinking is oftentimes treated as a black box, requiring input and producing creative output. Cognitive processes occurring during creative thinking tend to be neglected, although they can provide a bridge between the inputs to creativity and the resulting outputs. Literature offers different perspectives on creative thinking processes, such as the separation of divergent and convergent thinking, different stages of creativity or the concept of creative cognition. This variety of concepts underlying creativity has led to confusion and misinterpretations of some concepts. Moreover, the overemphasis on creative outcomes and divergent thinking has resulted in a neglect of a more comprehensive view on cognitive dimensions of creativity. Through reviewing and synthesizing multidisciplinary literature on creativity, an integrative framework is developed positioning cognitive elements of creativity within a system including organizational antecedents to creativity and creative outcomes. The framework seeks to offer pathways to increasingly incorporate the concept of creative cognition into future research. Suggesting different forms of creative cognition that individuals engage in during creative thought, this theoretical work further offers a theoretical development of creativity concepts that intends to inspire future research designs and facilitates cross-disciplinary knowledge transfer.     

Design for assembly meaning: a framework for designers to design products that support operator cognition during the assembly process

Cognition, Technology & Work - Designing assembly instructions is mostly considered to be a non-designer task. Hence, in many companies, it is performed by production planners or instructional...     

Relations between task and activity: elements for elaborating a framework for error analysis

The notion of error, when applied to an activity or the result of an activity, implies the notion of task: it expresses the deviation between the activity and the task being considered from an angle which is judged to be relevant. The task and the activity are the object of representations for the analyst (or specialist) and for the driver. Four representations are dealt with in this paper: the task and the activity for the specialist and the task and the activity for the driver. An interpretation is proposed for these tasks, and they are illustrated using some of the work already carried out in this field. The signification of deviations between these representations is then discussed, together with the advantage of studying these deviations in order to clarify error-producing mechanisms. Analysis in terms of task and activity raises methodological and practical problems which are touched upon; it does not exclude referring to psychological theoretical frameworks to which it is worthwhile linking it. This perspective raises questions which make it possible to enhance the study of errors: it could be completed at a later date by extending it to include other representation categories.     

Human activity recognition in artificial intelligence framework: a narrative review

Human activity recognition (HAR) has multifaceted applications due to its worldly usage of acquisition devices such as smartphones, video cameras, and its ability to capture human activity data. While electronic devices and their applications are steadily growing, the advances in Artificial intelligence (AI) have revolutionized the ability to extract deep hidden information for accurate detection and its interpretation. This yields a better understanding of rapidly growing acquisition devices, AI, and applications, the three pillars of HAR under one roof. There are many review articles published on the general characteristics of HAR, a few have compared all the HAR devices at the same time, and few have explored the impact of evolving AI architecture. In our proposed review, a detailed narration on the three pillars of HAR is presented covering the period from 2011 to 2021. Further, the review presents the recommendations for an improved HAR design, its reliability, and stability. Five major findings were: (1) HAR constitutes three major pillars such as devices, AI and applications; (2) HAR has dominated the healthcare industry; (3) Hybrid AI models are in their infancy stage and needs considerable work for providing the stable and reliable design. Further, these trained models need solid prediction, high accuracy, generalization, and finally, meeting the objectives of the applications without bias; (4) little work was observed in abnormality detection during actions; and (5) almost no work has been done in forecasting actions. We conclude that: (a) HAR industry will evolve in terms of the three pillars of electronic devices, applications and the type of AI. (b) AI will provide a powerful impetus to the HAR industry in future.

     

Information-theoretic framework for unsupervised activity classification

This article presents a mathematical framework based on information theory to compare multivariate sensory streams. Central to this approach is the notion of configuration: a set of distances between information sources, statistically evaluated for a given time span. As information distances capture simultaneously effects of physical closeness, intermodality, functional relationship and external couplings, a configuration can be interpreted as a signature for specific patterns of activity. This provides ways for comparing activity sequences by viewing them as points in an activity space. Results of experiments with an autonomous robot illustrate how this framework can be used to perform unsupervised activity classification.     

A framework for developing a daily activity and multimodal travel planner

There is a need to further explore ways to use Advanced Traveler Information Systems (ATIS) to encourage transit and ridesharing. One mechanism is to provide convenient travel itinerary information, not just for one trip, but for a day's travel. The formulation should consider time constraints, activity needs, real transit service parameters and the actual street system. Basic algorithmic development is needed to spur the private sector interest in such a product by demonstrating its utility. The activity travel planner will aid its user in planning his daily itinerary by arranging the sequence of stops, suggesting and possibly selecting stop locations, providing transit route and schedule information, and suggesting travel routes. This paper develops a framework for solving the Travel Itinerary Planning Problem (TIPP) which is a variant of the Traveling Salesman Problem (TSP). Implementation of the solution algorithm would be used to develop and test a prototype for an activity and travel planner.     

Learning with tensors: a framework based on convex optimization and spectral regularization

We present a framework based on convex optimization and spectral regularization to perform learning when feature observations are multidimensional arrays (tensors). We give a mathematical characterization of spectral penalties for tensors and analyze a unifying class of convex optimization problems for which we present a provably convergent and scalable template algorithm. We then specialize this class of problems to perform learning both in a transductive as well as in an inductive setting. In the transductive case one has an input data tensor with missing features and, possibly, a partially observed matrix of labels. The goal is to both infer the missing input features as well as predict the missing labels. For induction, the goal is to determine a model for each learning task to be used for out of sample prediction. Each training pair consists of a multidimensional array and a set of labels each of which corresponding to related but distinct tasks. In either case the proposed technique exploits precise low multilinear rank assumptions over unknown multidimensional arrays; regularization is based on composite spectral penalties and connects to the concept of Multilinear Singular Value Decomposition. As a by-product of using a tensor-based formalism, our approach allows one to tackle the multi-task case in a natural way. Empirical studies demonstrate the merits of the proposed methods.     

Learning in the framework of fuzzy lattices

A basis for rigorous versatile learning is introduced theoretically, that is the framework of fuzzy lattices or FL-framework for short, which proposes a synergetic combination of fuzzy set theory and lattice theory. A fuzzy lattice emanates from a conventional mathematical lattice by fuzzifying the inclusion order relation. Learning in the FL-framework can be effected by handling families of intervals, where an interval is treated as a single entity/block the way explained here. Illustrations are provided in a lattice defined on the unit-hypercube where a lattice interval corresponds to a conventional hyperbox. A specific scheme for learning by clustering is presented, namely σ-fuzzy lattice learning scheme or σ-FLL (scheme) for short, inspired from adaptive resonance theory (ART). Learning by the σ-FLL is driven by an inclusion measure σ of the corresponding Cartesian product to be introduced here. We delineate a comparison of the σ-FLL scheme with various neural-fuzzy and other models. Applications are shown to one medical data set and two benchmark data sets, where σ-FLL's capacity for treating efficiently real numbers as well as lattice-ordered symbols separately or jointly is demonstrated. Due to its efficiency and wide scope of applicability the σ-FLL scheme emerges as a promising learning scheme     

The embodied Web: embodied Web‐services interaction with an umbrella for augmented city experiences

This paper introduces the embodied Web, a new design paradigm for mobile devices. The embodied Web aims to provide an interface using real‐world embodied interaction to provide a computer‐augmented reality that accesses web services. This platform regards embodied interaction at three levels: operational level, activity level and social level; and is implemented with a combination of sensor, actuator and network connectivities. The platform is developed as a complex of hardware, software and network services. The implementation takes an approach of modularization of hardware, software and web services. As a practical prototype of the embodied Web, the Internet Umbrella Pileus was developed and tested. In contrast to the small screens of mobile devices, Pileus has a big screen on the underside of the umbrella, and it is operated by embodied interaction, including motion sensing of the device and location sensing of walking activities. Photo‐sharing and 3D map navigation is provided on the umbrella to expand the user's activity area. These services are provided by API hookups with Flickr and Google Earth. Pileus has been iteratively developed from user observations, design observations and intuitions and prototype evaluations. The umbrella was tested in a large urban environment (the city of Tokyo). Copyright © 2008 John Wiley & Sons, Ltd.     

The analysis of embodied communicative feedback in multimodal corpora: a prerequisite for behavior simulation

Communicative feedback refers to unobtrusive (usually short) vocal or bodily expressions whereby a recipient of information can inform a contributor of information about whether he/she is able and willing to communicate, perceive the information, and understand the information. This paper provides a theory for embodied communicative feedback, describing the different dimensions and features involved. It also provides a corpus analysis part, describing a first data coding and analysis method geared to find the features postulated by the theory. The corpus analysis part describes different methods and statistical procedures and discusses their applicability and the possible insights gained with these methods.     

润物无声大道简行——应用型本科师资建设的学习与认知

作为我国高等教育普及化和现代化的产物,应用型本科高校在国家实施教育强国的战略部署过程中显示出重要的作用和意义。新形势的发展使得应用型本科高校师资队伍建设面临一些新的问题和挑战,认识和应对问题和挑战的出发点还是其办学初衷和历史定位。由此分别从高校教师个体的职业价值理念视角和师资队伍建设管理规划层面进行了相关学习与探讨。     

Tropism-based cognition: a novel software architecture for agents in colonies

A novel architecture for agents in colonies has been developed in order to investigate certain forms of group interaction. Specifically, we are interested in the extent to which overall goals for a colony can be achieved when each agent is only aware of limited local goals, whether the architecture allows for emergence of unexpected behaviour, and whether explicit communication among agents facilitates or hinders task performance. The architecture supports several forms of learning. Large colonies of agents (as many as 100) have been studied in simulation experiments, where they carried out fetch-and-carry tasks in the presence of predators and with limited energy reserves. In addition, a physical colony of four agents has been fabricated with the same architecture, to ensure that the behaviours observed in simulation were also present in the hardware implementations.     

O-buffer: a framework for sample-based graphics

We present an innovative modeling and rendering primitive, called the O-buffer, as a framework for sample-based graphics. The 2D or 3D O-buffer is, in essence, a conventional image or a volume, respectively, except that samples are not restricted to a regular grid. A sample position in the O-buffer is recorded as an offset to the nearest grid point of a regular base grid (hence the name O-buffer). The O-buffer can greatly improve the expressive power of images and volumes. Image quality can be improved by storing more spatial information with samples and by avoiding multiple resamplings. It can be exploited to represent and render unstructured primitives, such as points, particles, and curvilinear or irregular volumes. The O-buffer is therefore a unified representation for a variety of graphics primitives and supports mixing them in the same scene. It is a semiregular structure which lends itself to efficient construction and rendering. O-buffers may assume a variety of forms including 2D O-buffers, 3D O-buffers, uniform O-buffers, nonuniform O-buffers, adaptive O-buffers, layered-depth O-buffers, and O-buffer trees. We demonstrate the effectiveness of the O--buffer in a variety of applications, such as image-based rendering, point sample rendering, and volume rendering.