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Implementation of Semantic Memory in a machine conscious system based on the CONAIM architecture

Grant number: 15/11768-2
Support Opportunities:Scholarships in Brazil - Scientific Initiation
Effective date (Start): December 01, 2015
Effective date (End): November 30, 2016
Field of knowledge:Engineering - Electrical Engineering - Industrial Electronics, Electronic Systems and Controls
Principal Investigator:Alexandre da Silva Simões
Grantee:Leonardo de Lellis Rossi
Host Institution: Instituto de Ciência e Tecnologia. Universidade Estadual Paulista (UNESP). Campus de Sorocaba. Sorocaba , SP, Brazil


Understanding consciousness is one of the most fascinating challenges of our time. From ancient civilizations to modern philosophers, questions have been asked on how one is conscious about his/her own existence and about the world that surrounds him/her. Although there is no precise definition for consciousness, there is an agreement that it is strongly related to human cognitive processes linked as a complex system. One of the key processes related to consciousness is attention, a cognitive process capable of promoting a selection of just a few stimuli among a huge number of information that reaches us constantly. In order to bring the consciousness discussion to a computational scenario, previous works presented CONAIM (Conscious Attention-based Integrated Model), a formal model for machine consciousness based on an attentional schema for human-like agent cognition that integrates: short and long term memories, reasoning, planning, emotion, decision making, learning, motivation and volition. Experimental results under a mobile robotics domain suggest that the agent can demonstrate awareness, sentience, self-awareness, self-consciousness, auto noetic consciousness, fineness, volition and perspectivalness based on exogenous and endogenous stimuli. By performing computation over an attentional space, the model also allowed the agent to learn over a 95% reduced space-state. This work proposes the development and computational implementation of the semantic memory of the CONAIM model.

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