14,277 research outputs found
Interaction and Experience in Enactive Intelligence and Humanoid Robotics
We overview how sensorimotor experience can be operationalized for interaction scenarios in which humanoid robots acquire skills and linguistic behaviours via enacting a âform-of-lifeââ in interaction games (following Wittgenstein) with humans. The enactive paradigm is introduced which provides a powerful framework for the construction of complex adaptive systems, based on interaction, habit, and experience. Enactive cognitive architectures (following insights of Varela, Thompson and Rosch) that we have developed support social learning and robot ontogeny by harnessing information-theoretic methods and raw uninterpreted sensorimotor experience to scaffold the acquisition of behaviours. The success criterion here is validation by the robot engaging in ongoing human-robot interaction with naive participants who, over the course of iterated interactions, shape the robotâs behavioural and linguistic development. Engagement in such interaction exhibiting aspects of purposeful, habitual recurring structure evidences the developed capability of the humanoid to enact language and interaction games as a successful participant
Tools for Thought: The Case of Mathematics
The objective of this article is to take into account the functioning of representational cognitive tools, and in particular of notations and visualizations in mathematics. In order to explain their functioning, formulas in algebra and logic and diagrams in topology will be presented as case studies and the notion of manipulative imagination as proposed in previous work will be discussed. To better characterize the analysis, the notions of material anchor and representational affordance will be introduced
Containing Systemic Risk
Systemic risk refers to the risk of financial system breakdown due to linkages between institutions. This risk cannot be assessed by looking at how individual institutions manage risks but instead requires a full understanding of how the system as a whole operates. At present, the data available to central banks and financial regulators are not at all adequate for the task of assessing systemic risk and the new European Systemic Risk Board needs to address this issue. There is a lot of exciting ongoing research devoted to measuring systemic risk and providing signals to regulators as to when and where they should intervene. However, the tools being developed are still limited in their usefulness. More pressing than the development of these tools is the development and implementation of policy measures to make the financial system more robust. These measures should include higher capital ratios, limits on non-core funding and redesigning financial systems to be less complex.Financial Risk,Systemic Risk,Banking
The VEX-93 environment as a hybrid tool for developing knowledge systems with different problem solving techniques
The paper describes VEX-93 as a hybrid environment for developing
knowledge-based and problem solver systems. It integrates methods and
techniques from artificial intelligence, image and signal processing and
data analysis, which can be mixed. Two hierarchical levels of reasoning
contains an intelligent toolbox with one upper strategic inference engine
and four lower ones containing specific reasoning models: truth-functional
(rule-based), probabilistic (causal networks), fuzzy (rule-based) and
case-based (frames). There are image/signal processing-analysis capabilities
in the form of programming languages with more than one hundred primitive
functions.
User-made programs are embeddable within knowledge basis, allowing the
combination of perception and reasoning. The data analyzer toolbox contains
a collection of numerical classification, pattern recognition and ordination
methods, with neural network tools and a data base query language at
inference engines's disposal.
VEX-93 is an open system able to communicate with external computer programs
relevant to a particular application. Metaknowledge can be used for
elaborate conclusions, and man-machine interaction includes, besides windows
and graphical interfaces, acceptance of voice commands and production of
speech output.
The system was conceived for real-world applications in general domains, but
an example of a concrete medical diagnostic support system at present under
completion as a cuban-spanish project is mentioned.
Present version of VEX-93 is a huge system composed by about one and half
millions of lines of C code and runs in microcomputers under Windows 3.1.Postprint (published version
Agents for educational games and simulations
This book consists mainly of revised papers that were presented at the Agents for Educational Games and Simulation (AEGS) workshop held on May 2, 2011, as part of the Autonomous Agents and MultiAgent Systems (AAMAS) conference in Taipei, Taiwan. The 12 full papers presented were carefully reviewed and selected from various submissions. The papers are organized topical sections on middleware applications, dialogues and learning, adaption and convergence, and agent applications
Constraint rule-based programming of norms for electronic institutions
Peer reviewedPostprin
Ethical Challenges in Data-Driven Dialogue Systems
The use of dialogue systems as a medium for human-machine interaction is an
increasingly prevalent paradigm. A growing number of dialogue systems use
conversation strategies that are learned from large datasets. There are well
documented instances where interactions with these system have resulted in
biased or even offensive conversations due to the data-driven training process.
Here, we highlight potential ethical issues that arise in dialogue systems
research, including: implicit biases in data-driven systems, the rise of
adversarial examples, potential sources of privacy violations, safety concerns,
special considerations for reinforcement learning systems, and reproducibility
concerns. We also suggest areas stemming from these issues that deserve further
investigation. Through this initial survey, we hope to spur research leading to
robust, safe, and ethically sound dialogue systems.Comment: In Submission to the AAAI/ACM conference on Artificial Intelligence,
Ethics, and Societ
Conflict and Computation on Wikipedia: a Finite-State Machine Analysis of Editor Interactions
What is the boundary between a vigorous argument and a breakdown of
relations? What drives a group of individuals across it? Taking Wikipedia as a
test case, we use a hidden Markov model to approximate the computational
structure and social grammar of more than a decade of cooperation and conflict
among its editors. Across a wide range of pages, we discover a bursty war/peace
structure where the systems can become trapped, sometimes for months, in a
computational subspace associated with significantly higher levels of
conflict-tracking "revert" actions. Distinct patterns of behavior characterize
the lower-conflict subspace, including tit-for-tat reversion. While a fraction
of the transitions between these subspaces are associated with top-down actions
taken by administrators, the effects are weak. Surprisingly, we find no
statistical signal that transitions are associated with the appearance of
particularly anti-social users, and only weak association with significant news
events outside the system. These findings are consistent with transitions being
driven by decentralized processes with no clear locus of control. Models of
belief revision in the presence of a common resource for information-sharing
predict the existence of two distinct phases: a disordered high-conflict phase,
and a frozen phase with spontaneously-broken symmetry. The bistability we
observe empirically may be a consequence of editor turn-over, which drives the
system to a critical point between them.Comment: 23 pages, 3 figures. Matches published version. Code for HMM fitting
available at http://bit.ly/sfihmm ; time series and derived finite state
machines at bit.ly/wiki_hm
Action-based effects on music perception
The classical, disembodied approach to music cognition conceptualizes action and perception as separate, peripheral processes. In contrast, embodied accounts of music cognition emphasize the central role of the close coupling of action and perception. It is a commonly established fact that perception spurs action tendencies. We present a theoretical framework that captures the ways in which the human motor system and its actions can reciprocally influence the perception of music. The cornerstone of this framework is the common coding theory, postulating a representational overlap in the brain between the planning, the execution, and the perception of movement. The integration of action and perception in so-called internal models is explained as a result of associative learning processes. Characteristic of internal models is that they allow intended or perceived sensory states to be transferred into corresponding motor commands (inverse modeling), and vice versa, to predict the sensory outcomes of planned actions (forward modeling). Embodied accounts typically refer to inverse modeling to explain action effects on music perception (Leman, 2007). We extend this account by pinpointing forward modeling as an alternative mechanism by which action can modulate perception. We provide an extensive overview of recent empirical evidence in support of this idea. Additionally, we demonstrate that motor dysfunctions can cause perceptual disabilities, supporting the main idea of the paper that the human motor system plays a functional role in auditory perception. The finding that music perception is shaped by the human motor system and its actions suggests that the musical mind is highly embodied. However, we advocate for a more radical approach to embodied (music) cognition in the sense that it needs to be considered as a dynamical process, in which aspects of action, perception, introspection, and social interaction are of crucial importance
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