claim

active

claim:information-flow-and-increase-must-be-understood-relative-to-subsystems-and-their-interaction-with-environment

Information flow and increase must be understood relative to subsystems and their interaction with environment.

Source paper

extracted_from

Information, Processes and Games

Abramsky, Samson

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Communities (3)

community

Design principles for care-centered systems
members_of
Cross-scale frameworks linking spatial patterns, diagrams, and simplicity as expressions of care in design.
Information dynamics in computational systems
members_of
Studies how information flow, increase, and explicitness emerge from computation relative to observers and subsystems, grounded in domain theory and order-theoretic formalism.
Observer-relative computational information theory
members_of
Information increase and flow reframed as subsystem- and observer-dependent, not absolute thermodynamic quantities.

Questions (1)

question

Does information increase in computation?
answered_by
Fundamental puzzle motivating the paper: how can computation produce new information when output is logically implied by input and thermodynamics suggests information cannot increase?

Related by similarity (8)

cosine ≥ 0.65 · no typed edge

Entities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.

Information can increase in computation only relative to subsystems and observersclaim0.870
The author argues that while total system information is conserved (thermodynamic), computation gains information for the observer by making implicit information explicit and discarding irrelevant data.
Information increase in computation is observer-dependent, relative to the computational direction chosen.claim0.819
Extension of information dynamics: direction of information increase (e.g., forward multiplication vs. reverse factorization) depends on observer's goals.
The direction of information increase is relative to the observer or user of the computationclaim0.814
Example: 3×5→15 is a natural computation, but 15→3×5 (prime factorization) is also useful, showing that the 'gain' depends on the choice of normal form.
Information increase in computation arises from data reduction and making implicit information explicit, not logical increase.claim0.801
Author's proposed resolution to the information increase paradox: computation gains utility through extraction and filtering, not creation of logically new content.
information increase in computationconcept0.793
The puzzle that computation appears to gain information despite logical closure; resolved by relative to subsystems/observers.
Agents and their interactions are intrinsic to studying information flow in computation, not peripheral to classical information theory.claim0.792
Central thesis: traditional static information theories fail to capture dynamic interaction necessary for understanding modern computing.
The fundamental objects of study in information dynamics should be open systems interacting with an environmentclaim0.777
Because information flow and increase are relative to subsystems, agents embedded in environments are the proper units of analysis.
How can information increase in computation if output is logically implied by input?question0.771