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\begin{document}

\title{Number of autonomous agents in a neural network}



\author[1]{Subhash Kak }%
\affil[1]{Oklahoma State University}%


\vspace{-1em}



  
  \date{May 24, 2024}


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\begin{abstract}
This paper considers several aspects of the relationship between size,
structure, speed of propagation and the number of autonomous cognitive
agents in a neural network. Whereas, memory and function generation
capacities of neural networks with scale invariant structure have been
investigated extensively, the number of autonomous agents has not
received prior attention. We propose the emergence of the dichotomy of
causal and noncausal regions that is related to speed of propagation, in
which the autonomous cognitive agents are not bound in a causal
relationship with other agents. Arguments are presented for why the
count of autonomous agents is best estimated with respect to the
dimensionality of the underlying space. The number of autonomous agents
obtained for the human brain equals twenty-five, and it is significant
that the number in the sub-system modules also turns out to be close to
the same value. It is possible that this near equality across layers
provides a special uniqueness to the human brain. We argue that the
findings of this study will be useful in the design of neural-network
based AI systems that are designed to emulate human cognitive
capacity.\\%
\end{abstract}%



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