claim

active

claim:information-increase-in-computation-arises-from-data-reduction-and-making-implicit-information-explicit-not-logical-increase

Information increase in computation arises from data reduction and making implicit information explicit, not logical increase.

Author's proposed resolution to the information increase paradox: computation gains utility through extraction and filtering, not creation of logically new content.

Source paper

extracted_from

Information, Processes and Games

Abramsky, Samson

Neighborhood — ranked by edge-count

Findings (1)

finding

Least Fixpoint Theorem: A continuous function f on an ω-cpo with least element has a unique least fixpoint definable as ⊔ f^n(⊥).
supports
Fundamental mathematical result in Domain Theory enabling rigorous treatment of recursive definitions and infinite computations as limits of finite information increase.

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.

Concepts (1)

concept

Geometry of Interaction
supports
Dynamic model connecting logic to geometry through explicit treatment of information flow and interaction; demonstrates emergent logical complexity from simple copy-cat processes.

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.

How can information increase in computation if output is logically implied by input?question0.876
information increase in computationconcept0.870
The puzzle that computation appears to gain information despite logical closure; resolved by relative to subsystems/observers.
Information increase in computation is observer-dependent, relative to the computational direction chosen.claim0.852
Extension of information dynamics: direction of information increase (e.g., forward multiplication vs. reverse factorization) depends on observer's goals.
Information can increase in computation only relative to subsystems and observersclaim0.848
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.
The direction of information increase is relative to the observer or user of the computationclaim0.805
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 flow and increase must be understood relative to subsystems and their interaction with environment.claim0.801
Making information explicit—extracting normal forms from computation.claim0.796
Why do we compute? The natural answer is: to gain information (which we did not previously have)! But how is this possible?concept0.787
Opening framing of the central puzzle driving the entire investigation into information dynamics.