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  1. Anna M. Borghi & Angelo Cangelosi (2014). Action and Language Integration: From Humans to Cognitive Robots. Topics in Cognitive Science 6 (3):344-358.
    The topic is characterized by a highly interdisciplinary approach to the issue of action and language integration. Such an approach, combining computational models and cognitive robotics experiments with neuroscience, psychology, philosophy, and linguistic approaches, can be a powerful means that can help researchers disentangle ambiguous issues, provide better and clearer definitions, and formulate clearer predictions on the links between action and language. In the introduction we briefly describe the papers and discuss the challenges they pose to future research. We identify (...)
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  2. Frank Broz, Chrystopher L. Nehaniv, Tony Belpaeme, Ambra Bisio, Kerstin Dautenhahn, Luciano Fadiga, Tomassino Ferrauto, Kerstin Fischer, Frank Förster, Onofrio Gigliotta, Sascha Griffiths, Hagen Lehmann, Katrin S. Lohan, Caroline Lyon, Davide Marocco, Gianluca Massera, Giorgio Metta, Vishwanathan Mohan, Anthony Morse, Stefano Nolfi, Francesco Nori, Martin Peniak, Karola Pitsch, Katharina J. Rohlfing, Gerhard Sagerer, Yo Sato, Joe Saunders, Lars Schillingmann, Alessandra Sciutti, Vadim Tikhanoff, Britta Wrede, Arne Zeschel & Angelo Cangelosi (2014). The ITALK Project: A Developmental Robotics Approach to the Study of Individual, Social, and Linguistic Learning. Topics in Cognitive Science 6 (3):534-544.
    This article presents results from a multidisciplinary research project on the integration and transfer of language knowledge into robots as an empirical paradigm for the study of language development in both humans and humanoid robots. Within the framework of human linguistic and cognitive development, we focus on how three central types of learning interact and co-develop: individual learning about one's own embodiment and the environment, social learning (learning from others), and learning of linguistic capability. Our primary concern is how these (...)
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  3. Kerstin Dautenhahn & Angelo Cangelosi (2012). Progress on Evolution of Communication and Interaction Studies. Interaction Studies 13 (1):1-6.
  4. Jose Fernando Fontanari & Angelo Cangelosi (2011). Cross-Situational and Supervised Learning in the Emergence of Communication. Interaction Studies 12 (1):119-133.
    Scenarios for the emergence or bootstrap of a lexicon involve the repeated interaction between at least two agents who must reach a consensus on how to name N objects using H words. Here we consider minimal models of two types of learning algorithms: cross-situational learning, in which the individuals determine the meaning of a word by looking for something in common across all observed uses of that word, and supervised operant conditioning learning, in which there is strong feedback between individuals (...)
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  5. Angelo Cangelosi (2009). Editorial on Evolution of Communication. Interaction Studies 10 (1):1-4.
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  6. Angelo Cangelosi (2008). Symposium on “A Multi-Methodological Approach to Language Evolution”. Mind and Society 7 (1):35-41.
    This symposium includes a selection of articles on the origins and evolution of language. These are extended version of selected papers presented at “EVOLANG6: The Sixth International Conference on the Evolution of Language” that was held in Rome in April 2006. This selection of papers provides a multi-methodological view of different approaches to, and theoretical explanations of, the evolution of language.
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  7. Angelo Cangelosi (2006). The Grounding and Sharing of Symbols. Pragmatics and Cognition 14 (2):275-286.
    The double function of language, as a social/communicative means, and as an individual/cognitive capability, derives from its fundamental property that allows us to internally re-represent the world we live in. This is possible through the mechanism of symbol grounding, i.e., the ability to associate entities and states in the external and internal world with internal categorical representations. The symbol grounding mechanism, as language, has both an individual and a social component. The individual component, called the “Physical Symbol Grounding“, refers to (...)
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  8. Angelo Cangelosi & Thomas Riga (2006). An Embodied Model for Sensorimotor Grounding and Grounding Transfer: Experiments With Epigenetic Robots. Cognitive Science 30 (4):673-689.
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  9. Angelo Cangelosi (2002). Language Evolution in Apes and Autonomous Agents. Behavioral and Brain Sciences 25 (5):622-623.
    Computational approaches based on autonomous agents share with new ape language research the same principles of dynamical system paradigms. A recent model for the evolution of symbolization and language in autonomous agents is briefly described in order to highlight the similarities between these two methodologies. The additional benefits of autonomous agent modeling in the field of language origin research are highlighted.
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  10. Angelo Cangelosi, Alberto Greco & Stevan Harnad (2002). Symbol Grounding and the Symbolic Theft Hypothesis. In A. Cangelosi & D. Parisi (eds.), Simulating the Evolution of Language. Springer-Verlag. 191--210.
    Scholars studying the origins and evolution of language are also interested in the general issue of the evolution of cognition. Language is not an isolated capability of the individual, but has intrinsic relationships with many other behavioral, cognitive, and social abilities. By understanding the mechanisms underlying the evolution of linguistic abilities, it is possible to understand the evolution of cognitive abilities. Cognitivism, one of the current approaches in psychology and cognitive science, proposes that symbol systems capture mental phenomena, and attributes (...)
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  11. Angelo Cangelosi & Domenico Parisi (2002). Computer Simulation: A New Scientific Approach to the Study of Language Evolution. In A. Cangelosi & D. Parisi (eds.), Simulating the Evolution of Language. Springer-Verlag. 3--28.
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  12. Domenico Parisi & Angelo Cangelosi (2002). A Unified Simulation Scenario for Language Development, Evolution and Historical Change. In A. Cangelosi & D. Parisi (eds.), Simulating the Evolution of Language. Springer-Verlag. 255--275.
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  13. Angelo Cangelosi & Domenico Parisi (1998). Concepts in Artificial Organisms. Behavioral and Brain Sciences 21 (1):68-69.
    Simulations with neural networks living in a virtual environment can be used to explore and test hypotheses concerning concepts and language. The advantages that result from this approach include (1) the notion that a concept can be precisely defined and examined, (2) that concepts can be studied in both nonverbal and verbal artificial organisms, and (3) concepts have properties that depend on the environment as well as on the organism's adaptive behavior in response to the environment.
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