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AGI Brain: A Learning and Decision Making Framework for Artificial General Intelligence Systems Based on Modern Control Theory

  • 2019
  • OriginalPaper
  • Chapter
Published in:
Author
Mohammadreza Alidoust
Published in
Artificial General Intelligence
Publisher
Springer International Publishing

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Abstract

In this paper a unified learning and decision making framework for artificial general intelligence (AGI) based on modern control theory is presented. The framework, called AGI Brain, considers intelligence as a form of optimality and tries to duplicate intelligence using a unified strategy. AGI Brain benefits from powerful modelling capability of state-space representation, as well as ultimate learning ability of the neural networks. The model emulates three learning stages of human being for learning its surrounding world. The model was tested on three different continuous and hybrid (continuous and discrete) Action/State/Output/Reward (ASOR) space scenarios in deterministic single-agent/multi-agent worlds. Successful simulation results demonstrate the multi-purpose applicability of AGI Brain in deterministic worlds.

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next chapter Augmented Utilitarianism for AGI Safety
Title
AGI Brain: A Learning and Decision Making Framework for Artificial General Intelligence Systems Based on Modern Control Theory
Author
Mohammadreza Alidoust
Copyright Year
2019
Book
Artificial General Intelligence

Print ISBN: 978-3-030-27004-9

Electronic ISBN: 978-3-030-27005-6

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-3-030-27005-6_1
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