By Alejandro G. Stankevicius, Marcela Capobianco (auth.), Leliane N. Barros, Marcelo Finger, Aurora T. Pozo, Gustavo A. Gimenénez-Lugo, Marcos Castilho (eds.)
This booklet constitutes the refereed lawsuits of the twenty first Brazilian Symposium on synthetic Intelligence, SBIA 2012, held in Curitiba, Brazil, in October 2012. The 23 revised complete papers provided have been rigorously reviewed and chosen from eighty one submissions. The papers hide the subsequent subject matters: wisdom illustration, laptop studying, desktop studying and laptop imaginative and prescient, agent-based and multi-agent platforms, robotics and language, in addition to constraints.
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Additional info for Advances in Artificial Intelligence - SBIA 2012: 21th Brazilian Symposium on Artificial Intelligence, Curitiba, Brazil, October 20-25, 2012. Proceedings
Debugging and Repair of OWL Ontologies. PhD thesis, University of Maryland (2006) 20. : Belief revision within fragments of propositional logic. In: Principles of Knowledge Representation and Reasoning (KR 2012). AAAI Press (2012) 21. : Base Revision for Ontology Debugging. S. br Abstract. The autonomous cognitive development paradigm applied to cognitive agent’s design assumes that no prior knowledge should be embedded while the agent’s cognitive system is conceived. The use of this paradigm is an attempt to avoid the symbol grounding problem faced by some cognitive agent designs.
We assume that the cognitive system of a sensorimotor agent is not aware of what it’s sensors sense or what it’s actuators do, or even where they are connected to in the agent’s body. Using these prerogatives we present a sensorimotor domain approach that can be used to build agent’s controls and to construct agents’ cognitive systems. This proposal is then compared to an approach for sensorimotor control system implementation, here called sensorimotor functional approach, under the perspective of the autonomous cognitive development paradigm.
In the SeMaps ontology, the marker has information about an event, a person, a business or a particular fact (represented by the concept classes created during the process of marker creation) and on the marker per se (such as date and time, the user who created it, among others). Moreover, in the marker there is a set of features to describe the provenance of the information, such as the type of source and how reliable it is. For representing these latter features, we imported the PML2 (Proof Markup Language) ontology .