58,245 research outputs found
The CHREST architecture of cognition : the role of perception in general intelligence
Original paper can be found at: http://www.atlantis-press.com/publications/aisr/AGI-10/ Copyright Atlantis Press. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited.This paper argues that the CHREST architecture of cognition can shed important light on developing artificial general intelligence. The key theme is that "cognition is perception." The description of the main components and mechanisms of the architecture is followed by a discussion of several domains where CHREST has already been successfully applied, such as the psychology of expert behaviour, the acquisition of language by children, and the learning of multiple representations in physics. The characteristics of CHREST that enable it to account for empirical data include: self-organisation, an emphasis on cognitive limitations, the presence of a perception-learning cycle, and the use of naturalistic data as input for learning. We argue that some of these characteristics can help shed light on the hard questions facing theorists developing artificial general intelligence, such as intuition, the acquisition and use of concepts and the role of embodiment
Mapping Big Data into Knowledge Space with Cognitive Cyber-Infrastructure
Big data research has attracted great attention in science, technology,
industry and society. It is developing with the evolving scientific paradigm,
the fourth industrial revolution, and the transformational innovation of
technologies. However, its nature and fundamental challenge have not been
recognized, and its own methodology has not been formed. This paper explores
and answers the following questions: What is big data? What are the basic
methods for representing, managing and analyzing big data? What is the
relationship between big data and knowledge? Can we find a mapping from big
data into knowledge space? What kind of infrastructure is required to support
not only big data management and analysis but also knowledge discovery, sharing
and management? What is the relationship between big data and science paradigm?
What is the nature and fundamental challenge of big data computing? A
multi-dimensional perspective is presented toward a methodology of big data
computing.Comment: 59 page
A Vortex Method for Bi-phasic Fluids Interacting with Rigid Bodies
We present an accurate Lagrangian method based on vortex particles,
level-sets, and immersed boundary methods, for animating the interplay between
two fluids and rigid solids. We show that a vortex method is a good choice for
simulating bi-phase flow, such as liquid and gas, with a good level of realism.
Vortex particles are localized at the interfaces between the two fluids and
within the regions of high turbulence. We gain local precision and efficiency
from the stable advection permitted by the vorticity formulation. Moreover, our
numerical method straightforwardly solves the two-way coupling problem between
the fluids and animated rigid solids. This new approach is validated through
numerical comparisons with reference experiments from the computational fluid
community. We also show that the visually appealing results obtained in the CG
community can be reproduced with increased efficiency and an easier
implementation
Agent-based models and individualism: is the world agent-based?
Agent-based models (ABMs) are an increasingly popular tool in the social sciences. This trend seems likely to continue, so that they will become widely used in geography and in urban and regional planning. We present an overview of examples of these models in the life sciences, economics, planning, sociology, and archaeology. We conclude that ABMs strongly tend towards an individualist view of the social world. This point is reinforced by closer consideration of particular examples. This discussion pays attention to the inadequacy of an individualist model of society with reference to debates in social theory. We argue that because models are closed representations of an open world it is important that institutions and other social structures be explicitly included, or that their omission be explained. A tentative explanation for the bias of ABMs is offered, based on an examination of early research in artificial intelligence and distributed artificial intelligence from which disciplines the approach is derived. Some implications of these findings are discussed. We indicate some useful research directions which are beginning to tackle the individualism issue directly. We further note that the underlying assumptions of ABMs are often hidden in the implementation details. We conclude that such models must be subject to critical examination of their assumptions, and that model builders should engage with social theory if the approach is to realise its full potential
Mechanisms for the generation and regulation of sequential behaviour
A critical aspect of much human behaviour is the generation and regulation of sequential activities. Such behaviour is seen in both naturalistic settings such as routine action and language production and laboratory tasks such as serial recall and many reaction time experiments. There are a variety of computational mechanisms that may support the generation and regulation of sequential behaviours, ranging from those underlying Turing machines to those employed by recurrent connectionist networks. This paper surveys a range of such mechanisms, together with a range of empirical phenomena related to human sequential behaviour. It is argued that the empirical phenomena pose difficulties for most sequencing mechanisms, but that converging evidence from behavioural flexibility, error data arising from when the system is stressed or when it is damaged following brain injury, and between-trial effects in reaction time tasks, point to a hybrid symbolic activation-based mechanism for the generation and regulation of sequential behaviour. Some implications of this view for the nature of mental computation are highlighted
Quantum Simulation Logic, Oracles, and the Quantum Advantage
Query complexity is a common tool for comparing quantum and classical
computation, and it has produced many examples of how quantum algorithms differ
from classical ones. Here we investigate in detail the role that oracles play
for the advantage of quantum algorithms. We do so by using a simulation
framework, Quantum Simulation Logic (QSL), to construct oracles and algorithms
that solve some problems with the same success probability and number of
queries as the quantum algorithms. The framework can be simulated using only
classical resources at a constant overhead as compared to the quantum resources
used in quantum computation. Our results clarify the assumptions made and the
conditions needed when using quantum oracles. Using the same assumptions on
oracles within the simulation framework we show that for some specific
algorithms, like the Deutsch-Jozsa and Simon's algorithms, there simply is no
advantage in terms of query complexity. This does not detract from the fact
that quantum query complexity provides examples of how a quantum computer can
be expected to behave, which in turn has proved useful for finding new quantum
algorithms outside of the oracle paradigm, where the most prominent example is
Shor's algorithm for integer factorization.Comment: 48 pages, 46 figure
Emerging technologies in physics education
Three emerging technologies in physics education are evaluated from the
interdisciplinary perspective of cognitive science and physics education
research. The technologies - Physlet Physics, the Andes Intelligent Tutoring
System (ITS), and Microcomputer-Based Laboratory (MBL) Tools - are assessed
particularly in terms of their potential at promoting conceptual change,
developing expert-like problem-solving skills, and achieving the goals of the
traditional physics laboratory. Pedagogical methods to maximize the potential
of each educational technology are suggested.Comment: Accepted for publication in the Journal of Science Education and
Technology; 20 page
Schwinger pair production with ultracold atoms
We consider a system of ultracold atoms in an optical lattice as a quantum
simulator for electron-positron pair production in quantum electrodynamics
(QED). For a setup in one spatial dimension, we investigate the nonequilibrium
phenomenon of pair production including the backreaction leading to plasma
oscillations. Unlike previous investigations on quantum link models, we focus
on the infinite-dimensional Hilbert space of QED and show that it may be well
approximated by experiments employing Bose-Einstein condensates interacting
with fermionic atoms. The calculations based on functional integral techniques
give a unique access to the physical parameters required to realize the QED
phenomena in a cold atom experiment. In particular, we use our approach to
consider quantum link models in a yet unexplored parameter regime and give
bounds for their ability to capture essential features of the physics. The
results suggest a paradigmatic change towards realizations using coherent
many-body states rather than single atoms for quantum simulations of
high-energy particle physics phenomena.Comment: 5 pages, 4 figures, PLB versio
Simulating activities: Relating motives, deliberation, and attentive coordination
Activities are located behaviors, taking time, conceived as socially meaningful, and usually involving interaction with tools and the environment. In modeling human cognition as a form of problem solving (goal-directed search and operator sequencing), cognitive science researchers have not adequately studied “off-task” activities (e.g., waiting), non-intellectual motives (e.g., hunger), sustaining a goal state (e.g., playful interaction), and coupled perceptual-motor dynamics (e.g., following someone). These aspects of human behavior have been considered in bits and pieces in past research, identified as scripts, human factors, behavior settings, ensemble, flow experience, and situated action. More broadly, activity theory provides a comprehensive framework relating motives, goals, and operations. This paper ties these ideas together, using examples from work life in a Canadian High Arctic research station. The emphasis is on simulating human behavior as it naturally occurs, such that “working” is understood as an aspect of living. The result is a synthesis of previously unrelated analytic perspectives and a broader appreciation of the nature of human cognition. Simulating activities in this comprehensive way is useful for understanding work practice, promoting learning, and designing better tools, including human-robot systems
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