of Meanings in Living and Artificial Agents
Comenius University, Bratislava
Submitted in August 2007, defended June 2008.
Author: RNDr. Martin Takáč
Supervisor: Doc. RNDr. Ľubica Beňušková,
This thesis addresses the issues of the nature and origin of
understanding and meanings in language with the computational modeling
methodology. It reviews formal semantic theories, studies meanings in
living organisms within their evolutionary context and takes into
account empirical findings about language acquisition by children. It
analyzes meanings in existing computational systems with respect to
grounding in interaction with real or simulated environments. The main
contributions of the thesis follow:
First, we define a new original semantics based on so-called
identification criteria. The semantics allows for representation of
objects, properties, relations, changes, complex situations and events.
All meanings can be constructed by extracting cross-situational
similarities among instances of a category. Both the theory and
mechanisms of meaning construction are specified rigorously enough to
allow for implementation in computational models.
Second, we present two computational models of interaction-grounded
meaning construction. In the model of individual category construction,
the instances are grouped to categories by common motor programs
(affordances), while in the model of social learning, focused on the
influence of naming on category formation, entities are considered
members of the same category, if they are labeled with the same word by
an external teacher. Results of experimenting with both models validate
the proposed meaning-formation mechanisms.
Third, we report and analyze simulation results of an experiment
focused on the dynamics of meanings in iterated intergenerational
modeling. Cognitive semantics. Symbol grounding. Automated concept
formation. Language acquisition.
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