scholarly journals Metabolic limits on classical information processing by biological cells

Biosystems ◽  
2021 ◽  
pp. 104513
Author(s):  
Chris Fields ◽  
Michael Levin
2019 ◽  
Author(s):  
Gaëlle Vallée-Tourangeau ◽  
Frédéric Vallée-Tourangeau

We argue that a radical departure from the classical information-processing model is untenable because higher-level cognition is fundamentally representation-based. However, we also argue that classical accounts of thinking put too great an emphasis on the role of internal representations and mental processing. Manuscript accepted for publication in Cybernetics & Human Knowing available at https://www.ingentaconnect.com/content/imp/chk/2014/00000021/F0020001/art00009. This article may not exactly replicate the final version published in the journal. It is not the copy of the record.


2012 ◽  
Vol 12 (5&6) ◽  
pp. 395-403
Author(s):  
Jan Bouda ◽  
Matej Pivoluska ◽  
Martin Plesch

The lack of perfect randomness can cause significant problems in securing communication between two parties. McInnes and Pinkas \cite{McInnesPinkas-ImpossibilityofPrivate-1991} proved that unconditionally secure encryption is impossible when the key is sampled from a weak random source. The adversary can always gain some information about the plaintext, regardless of the cryptosystem design. Most notably, the adversary can obtain full information about the plaintext if he has access to just two bits of information about the source (irrespective on length of the key). In this paper we show that for every weak random source there is a cryptosystem with a classical plaintext, a classical key, and a quantum ciphertext that bounds the adversary's probability $p$ to guess correctly the plaintext strictly under the McInnes-Pinkas bound, except for a single case, where it coincides with the bound. In addition, regardless of the source of randomness, the adversary's probability $p$ is strictly smaller than $1$ as long as there is some uncertainty in the key (Shannon/min-entropy is non-zero). These results are another demonstration that quantum information processing can solve cryptographic tasks with strictly higher security than classical information processing.


Author(s):  
Jelena Vuckovic ◽  
Arka Majumdar ◽  
Erik Kim ◽  
Michal Bajcsy ◽  
Alexander Papageorge ◽  
...  

Author(s):  
Enrique Fernandez-Blanco ◽  
J. Andrés Serantes

From the unicellular to the more complex pluricellular organism needs to process the signals from its environment to survive. The computation science has already observed, that fact could be demonstrated remembering the artificial neural networks (ANN). This computation tool is based on the nervous system of the animals, but not only the nervous cells process information in an organism. Every cell has to process the development and functioning plan encoded at its DNA and every one of these cells executes this program in parallel with the others. Another interesting characteristic of natural cells is that they form systems that are tolerant to partial failures: small errors do not induce a global collapse of the system. The present work proposes a model that is based on DNA information processing, but adapting it to general information processing. This model can be based on a set of techniques called Artificial Embryogeny (Stanley K. & Miikkulainen R. 2003) which adapts characteristics from the biological cells to solve different problems.


2018 ◽  
Author(s):  
Gaëlle Vallée-Tourangeau ◽  
Frédéric Vallée-Tourangeau

In this working paper, we review the limitations of the classical information processing model to account for entrepreneurial cognition. We then introduce a different theoretical framework, SysTM, or systemic thinking model, which places agents-environments interactions at the core of cognitive activities. We discuss how this alternative may inform future work on entrepreneurial cognition.


2019 ◽  
Author(s):  
Gaëlle Vallée-Tourangeau ◽  
Frédéric Vallée-Tourangeau

In this chapter, we propose a systemic model of thinking (SysTM) to account for higher cognitive operations such as how an agent makes inferences, solves problems and makes decisions. The SysTM model conceives thinking as a cognitive process that evolves in time and space and results in a new cognitive event (i.e., a new solution to a problem). This presupposes that such cognitive events are emerging from cognitive interactivity, which we define as the meshed network of reciprocal causations between an agent’s mental processing and the transformative actions she applies to her immediate environment to achieve a cognitive result. To explain how cognitive interactivity results in cognitive events, SysTM builds upon the classical information processing model but breaks from the view that cognitive events result from a linear information processing path originating in the perception of a problem stimulus that is mentally processed to produce a cognitive event. Instead, SysTM holds that information processing in thinking evolves through a succession of deductive and inductive processing loops. Both loops give rise to transformative actions on the physical information layout, resulting in new perceptual inputs which inform the next processing loop. Such actions result from the enaction of mental action plans in deductive loops and from unplanned direct perception of action possibilities or affordances in inductive loops. To account for direct perception, we introduce the concept of an affordance pool to refer to a short term memory storage of action possibilities in working memory. We conclude by illustrating how SysTM can be used to derive new predictions and guide the study of cognitive interactivity in thinking.


Author(s):  
Joseph M. Renes

Information processing protocols are typically built out of simpler parts, called primitives, and two of the most important such primitives are privacy amplification (PA) and data compression. The former extracts the truly secret part of some classical data, while the latter squeezes it into the smallest possible form. We show these tasks are dual in the setting of quantum information processing. Specifically, the tasks of PA of classical information against quantum adversaries and classical data compression with quantum side information are dual in the sense that the ability to perform one implies the ability to perform the other. The duality arises because the two protocols are connected by complementarity and the uncertainty principle in the quantum setting. Applications include a new uncertainty principle formulated in terms of smooth min- and max-entropies, which are useful in the study of one-shot protocols, as well as new conditions for approximate quantum error correction.


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