The Origin and Evolution of Information Handling in Primordial Environments

Kernekoncepter

The origin and early evolution of information handling, from simple chemical automata to more complex molecular computers, can be explained by the sequential emergence of different classes of computational automata, from finite-state automata to Turing machines.

Resumé

The article explores the origin and early evolution of information handling in pre-biological environments, focusing on the sequential emergence of different classes of computational automata.
The authors start by describing how simple bimolecular reactions can be seen as finite-state automata (FSAs) capable of information processing (computation) through self-replication. These trivial replicators kick off the origin of information processing.
Next, the authors explain how the interaction of these FSAs can lead to the appearance of one-stack push-down automata (PDAs), which introduce information storage (memory) capabilities. This transition to PDAs allows for the development of more complex instructions and self-preserving behavior, leading to the emergence of "ante-organisms" capable of primitive evolution.
The authors then describe how the complexification of PDAs or the coupling of multiple PDAs can result in the appearance of limited-bounded automata (LBAs), which can transmit information (communication). This era sees the emergence of compartmentalization and digital messengers, paving the way for the advent of "proto-organisms" capable of gene-based Darwinian evolution.
The authors argue that this sequential/hierarchical origin of information handling, from FSAs to PDAs to LBAs, can explain how information control emerged ab initio and how primitive control mechanisms in life might have evolved, becoming increasingly refined. The authors also discuss how their narrative can be extended to explore biological phenomena at multiple spatial and temporal scales using different models of computation.

Statistik

"A major challenge when describing the origin of life is to explain how instructional information control systems emerge naturally and spontaneously from mere molecular dynamics."
"Chemical reactions can be thought of as molecular recognition machines, which do not need biochemistry to mimic the behavior of automata belonging to different classes."
"FSAs demarcate the origin of information processing (computation), PDAs define the appearance of information storage (memory) and LBAs bound the emergence of information transmission (communication)."
"The undecidability behind self-replication lead us explicitly to open-ended evolution."
"Since undecidability is plausible in the computational classes of PDA and LBA, the entities can still self-replicate by the mechanism previously described."

Citater

"The real challenge when describing life's origin is to explain how instructional information control systems emerge naturally and spontaneously from simple molecular dynamics."
"By elucidating the origin and early evolution of information handling by chemical automata, we explain how information control emerged ab initio and how primitive control mechanisms in life might have evolved."
"The possibility of characterizing the different levels of complexification in life may well be related to the major transitions in evolution."

Vigtigste indsigter udtrukket fra

The Origin of Information Handling

by Amah... kl. arxiv.org 04-09-2024

https://arxiv.org/pdf/2404.04374.pdf

Dybere Forespørgsler

How can the proposed narrative be experimentally validated, both in vitro and in silico, to provide further support for the hypothesized emergence and evolution of information handling in pre-biological environments?

The proposed narrative can be experimentally validated through a combination of in vitro and in silico experiments. In vitro experiments could involve the synthesis of chemical components and reactions described in the narrative, mimicking the classes of chemical automata proposed. For instance, vesicles could be synthesized using different chemical reactions to represent the various stages of automata evolution. By observing the abilities and behaviors of these synthetic systems, researchers can assess how well they align with the hypothesized emergence and evolution of information handling in pre-biological environments.
In silico experiments could involve computational simulations based on the theoretical framework presented in the narrative. By modeling the interactions and dynamics of the chemical automata using computational tools, researchers can simulate the evolution of these systems over time. These simulations can provide insights into the plausibility and feasibility of the proposed narrative, allowing for the exploration of different scenarios and conditions that may not be easily achievable in laboratory settings.
By combining both experimental approaches, researchers can gather empirical data and computational insights to validate and refine the proposed narrative of information handling emergence and evolution in pre-biological environments.

What are the potential limitations or counterarguments to the authors' perspective that information handling can arise independently of the specific chemical substrate, and how could these be addressed?

One potential limitation or counterargument to the authors' perspective is the specificity of the chemical reactions and components proposed in the narrative. Critics may argue that the emergence of information handling could be highly dependent on the particular characteristics of the chemical substrate used in the experiments. To address this, researchers could explore alternative chemical systems or reactions to test the robustness and generalizability of the proposed narrative. By demonstrating that similar information handling mechanisms can arise from different chemical substrates, researchers can strengthen the argument for the independence of information handling from specific chemical compositions.
Another counterargument could be the complexity of scaling up from simple chemical systems to biological organisms. Critics may question the feasibility of transitioning from chemical automata to complex life forms based on the proposed narrative. To address this, researchers could conduct experiments or simulations that bridge the gap between simple chemical systems and more complex biological entities. By demonstrating incremental steps in the evolution of information handling mechanisms, researchers can provide a more convincing argument for the plausibility of the proposed narrative.

Given the authors' emphasis on the importance of undecidability in driving open-ended evolution, how might this concept be further explored in the context of the origin and evolution of life from a computational perspective?

The concept of undecidability in driving open-ended evolution can be further explored in the context of the origin and evolution of life from a computational perspective by investigating the role of computational complexity in biological systems. Researchers could analyze how undecidable problems, such as the Halting problem, manifest in biological processes and contribute to the diversity and adaptability of living organisms.
By studying the computational aspects of biological systems, researchers can identify patterns of undecidability that lead to emergent properties and behaviors in organisms. This exploration could involve modeling biological processes as computational tasks and analyzing the implications of undecidability on the evolution of complexity and diversity in living systems.
Furthermore, researchers could investigate how different levels of computational complexity, from simple automata to more advanced computational models, contribute to the emergence of life-like properties. By integrating computational theory with biological principles, researchers can gain a deeper understanding of how undecidability shapes the evolution of life and the development of complex organisms.