63,927 research outputs found
Human Computation and Convergence
Humans are the most effective integrators and producers of information,
directly and through the use of information-processing inventions. As these
inventions become increasingly sophisticated, the substantive role of humans in
processing information will tend toward capabilities that derive from our most
complex cognitive processes, e.g., abstraction, creativity, and applied world
knowledge. Through the advancement of human computation - methods that leverage
the respective strengths of humans and machines in distributed
information-processing systems - formerly discrete processes will combine
synergistically into increasingly integrated and complex information processing
systems. These new, collective systems will exhibit an unprecedented degree of
predictive accuracy in modeling physical and techno-social processes, and may
ultimately coalesce into a single unified predictive organism, with the
capacity to address societies most wicked problems and achieve planetary
homeostasis.Comment: Pre-publication draft of chapter. 24 pages, 3 figures; added
references to page 1 and 3, and corrected typ
Bat Algorithm: Literature Review and Applications
Bat algorithm (BA) is a bio-inspired algorithm developed by Yang in 2010 and
BA has been found to be very efficient. As a result, the literature has
expanded significantly in the last 3 years. This paper provides a timely review
of the bat algorithm and its new variants. A wide range of diverse applications
and case studies are also reviewed and summarized briefly here. Further
research topics are also discussed.Comment: 10 page
Reclaiming human machine nature
Extending and modifying his domain of life by artifact production is one of
the main characteristics of humankind. From the first hominid, who used a wood
stick or a stone for extending his upper limbs and augmenting his gesture
strength, to current systems engineers who used technologies for augmenting
human cognition, perception and action, extending human body capabilities
remains a big issue. From more than fifty years cybernetics, computer and
cognitive sciences have imposed only one reductionist model of human machine
systems: cognitive systems. Inspired by philosophy, behaviorist psychology and
the information treatment metaphor, the cognitive system paradigm requires a
function view and a functional analysis in human systems design process.
According that design approach, human have been reduced to his metaphysical and
functional properties in a new dualism. Human body requirements have been left
to physical ergonomics or "physiology". With multidisciplinary convergence, the
issues of "human-machine" systems and "human artifacts" evolve. The loss of
biological and social boundaries between human organisms and interactive and
informational physical artifact questions the current engineering methods and
ergonomic design of cognitive systems. New developpment of human machine
systems for intensive care, human space activities or bio-engineering sytems
requires grounding human systems design on a renewed epistemological framework
for future human systems model and evidence based "bio-engineering". In that
context, reclaiming human factors, augmented human and human machine nature is
a necessityComment: Published in HCI International 2014, Heraklion : Greece (2014
A Psychogenetic Algorithm for Behavioral Sequence Learning
This work presents an original algorithmic model of some essential features of psychogenetic theory, as was proposed by J.Piaget. Specifically, we modeled some elements of cognitive structure learning in children from 0 to 4 months of life. We are in fact convinced that the study of well-established cognitive models of human learning can suggest new, interesting approaches to problem so far not satisfactorily solved in the field of machine learning. Further, we discussed the possible parallels between our model and subsymbolic machine learning and neuroscience. The model was implemented and tested in some simple experimental settings, with reference to the task of learning sensorimotor sequences
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