Belief functions in computational linguistics: a reconsideration of belief modes
DOI:
https://doi.org/10.35494/topsem.2016.2.36.451Keywords:
theory of evidence, artificial agent, speech recognition, conversational agentsAbstract
Proposed as a core element for a probabilistic model, belief
functions are aimed at representing the beliefs an artificial agent
or subject produces as it observes the world. Although such a
construct has been successfully applied in a number of scientific
fields, most of its applications in the design of artificial
agents have exploited the modality of believing using only a
few of all of its possible modes of expression. This has recently
changed with a number of current computational linguistics
applications which employ all modes of believing for this
cognitive modality. The expansion in the use of the modes of
believing for the design of artificial agents has resulted in an
improvement of the performance by these computational linguistics
applications. These results confirm the current validity
of Greimas’ warning as to not to ignore this cognitive modality.
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