2,901 research outputs found

    Neurocognitive Informatics Manifesto.

    Get PDF
    Informatics studies all aspects of the structure of natural and artificial information systems. Theoretical and abstract approaches to information have made great advances, but human information processing is still unmatched in many areas, including information management, representation and understanding. Neurocognitive informatics is a new, emerging field that should help to improve the matching of artificial and natural systems, and inspire better computational algorithms to solve problems that are still beyond the reach of machines. In this position paper examples of neurocognitive inspirations and promising directions in this area are given

    Adaptive Translation : Finding Interlingual Mappings Using Self-Organizing Maps

    Get PDF
    Volume: 5163This paper presents a method for creating interlingual word-to-word or phrase-to-phrase mappings between any two languages using the self-organizing map algorithm. The method can be used as a component in a statistical machine translation system. The conceptual space created by the self-organizing map serves as a kind of interlingual representation. The specific problems of machine translation are discussed in some detail. The proposed method serves in alleviating two problems. The main problem addressed here is the fact that different languages divide the conceptual space differently. The approach can also help in dealing with lexical ambiguity.Peer reviewe

    Neurons and Symbols: A Manifesto

    Get PDF
    We discuss the purpose of neural-symbolic integration including its principles, mechanisms and applications. We outline a cognitive computational model for neural-symbolic integration, position the model in the broader context of multi-agent systems, machine learning and automated reasoning, and list some of the challenges for the area of neural-symbolic computation to achieve the promise of effective integration of robust learning and expressive reasoning under uncertainty

    Conceptual Representations for Computational Concept Creation

    Get PDF
    Computational creativity seeks to understand computational mechanisms that can be characterized as creative. The creation of new concepts is a central challenge for any creative system. In this article, we outline different approaches to computational concept creation and then review conceptual representations relevant to concept creation, and therefore to computational creativity. The conceptual representations are organized in accordance with two important perspectives on the distinctions between them. One distinction is between symbolic, spatial and connectionist representations. The other is between descriptive and procedural representations. Additionally, conceptual representations used in particular creative domains, such as language, music, image and emotion, are reviewed separately. For every representation reviewed, we cover the inference it affords, the computational means of building it, and its application in concept creation.Peer reviewe

    Japan fuzzified: the development of fuzzy logic research in Japan

    Get PDF
    corecore