Jean-louis Dessalles - Online papers

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SIMPLICITY:Simplicity Theory
EVOL.&LANG.:Evolutionary origins of language and of cognition
NARRATIVE:Cognitive modelling of interest in conversational narratives
ARGUMENTATION:Cognitive modelling of relevance in argumentative discussions
MEANING:Cognitive modelling of meaning
CONVERSATION:Cognitive modelling of spontaneous conversation
EMOTION:Cognitive modelling of emotional intensity
LEARNING:Cognitive modelling of concept learning
CONSCIOUSNESS:Qualia cannot be epiphenomenal (but the expl. gap is intact)
EMERGENCE:Emergence as complexity drop
EVOL.&INFORM.:Evolution and information

Selected Papers (but see my other papers)

  1. Dessalles, J.-L. (2016). A Cognitive Approach to Relevant Argument Generation. In M. Baldoni, C. Baroglio, F. Bex, T. D. Bui, F. Grasso & et al. (Eds.), Principles and Practice of Multi-Agent Systems, LNAI 9935, 3-15. Springer.
    Acceptable arguments must be logically relevant. This paper describes an attempt to retro-engineer the human argumentative competence. The aim is to produce a minimal cognitive procedure that generates logically relevant arguments at the right time. Such a procedure is proposed as a proof of principle. It relies on a very small number of operations that are systematically performed: logical conflict detection, abduction and negation. Its eventual vali-dation however depends on the quality of the available domain knowledge.

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  2. Dessalles, J.-L. (2015). From conceptual spaces to predicates. In F. Zenker & P. Gärdenfors (Eds.), Applications of conceptual spaces: The case for geometric knowledge representation, 17-31. Dordrecht: Springer.
    Keywords: MEANING
    Why is a red face not really red? How do we decide that this book is a textbook or not? Conceptual spaces provide the medium on which these computations are performed, but an additional operation is needed: Contrast.

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  3. Saillenfest, A. & Dessalles, J.-L. (2015). Some probability judgments may rely on complexity assessments. Proceedings of the 37th Annual Conference of the Cognitive Science Society, 2069-2074. Austin, TX: Cognitive Science Society.
    Keywords: SIMPLICITY
    Human beings do assess probabilities. Their judgments are however sometimes at odds with probability theory. One possibility is that human cognition is imperfect or flawed in the probability domain, showing biases and errors. Another possibility, that we explore here, is that human probability judgments do not rely on a weak version of probability calculus, but rather on complexity computations. This hypothesis is worth exploring, not only because it predicts some of the probability ‘biases’, but also because it explains human judgments of uncertainty in cases where probability calculus cannot be applied. We designed such a case in which the use of complexity when judging uncertainty is almost transparent.

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    Video of the talk
  4. Dessalles, J.-L. (2014). Optimal Investment in Social Signals. Evolution, 68 (6), 1640-1650.
    Keywords: EVOL.&LANG.
    This study is an attempt to determine how much individuals should invest in social communication, depending on the type of relationships they may form. Two simple models of social relationships are considered. In both models, individuals emit costly signals to advertise their "quality" as potential friends. Relationships are asymmetrical or symmetrical. In the asymmetrical condition (first model), we observe that low-quality individuals are discouraged from signaling. In the symmetrical condition (second model), all individuals invest in communication. In both models, high-quality individuals ("elite") do not compete and signal uniformly. The level of this uniform signal and the size of the “elite” turn out to be controlled by the accuracy of signals. The two models may be relevant to several aspects of animal and human social communication.

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  5. Dessalles, J.-L. (2014). Why talk? In D. Dor, C. Knight & J. Lewis (Eds.), The social origins of language, 284-296. Oxford, UK: Oxford University Press.
    Keywords: EVOL.&LANG.
    What is language good for? For a long time, the question has remained not only unanswered, but not even asked. The classic ‘reason’ invoked to avoid the issue was that language benefited the species as a whole. This way of reasoning is simply wrong (Williams 1966). If information has any value, it is in the interest of no one to give it for free. And if information has no value, why are there ears ready to listen to it? The reason why we talk, and so much, still requires a biological and social explanation.

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  6. Dessalles, J.-L. (2013). Algorithmic simplicity and relevance. In D. L. Dowe (Ed.), Algorithmic probability and friends - LNAI 7070, 119-130. Berlin, D: Springer Verlag.
    The human mind is known to be sensitive to complexity. For instance, the visual system reconstructs hidden parts of objects following a principle of maximum simplicity. We suggest here that higher cognitive processes, such as the selection of relevant situations, are sensitive to variations of complexity. Situations are relevant to human beings when they appear simpler to describe than to generate. This definition offers a predictive (i.e. refutable) model for the selection of situations worth reporting (interestingness) and for what individuals consider an appropriate move in conversation.

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