Research

A map of questions, with the ancestors left visible.

The programme asks how cognitive tools can enlarge the set of worthwhile futures that humans and institutions can actually reach. It starts from established work on search, adjacent possibilities, attention, knowledge uptake and distributed discovery rather than pretending those ideas appeared here first.

Meta aim

The goal is not more ideas. It is greater capacity to reach worthwhile futures.

The adjacent possible is an established idea, and Taalbi already uses the term effective adjacent possible for the subset constrained by search and absorptive capacity. Agalmic Research asks what machine cognition, representation, validation, provenance and realization infrastructure do to that effective frontier.

Novelty posture

Search before naming a field.

Agalmic Research distinguishes established antecedents, independent rediscovery, synthesis, extension, application, operationalization and genuinely unassessed novelty.

The reviews have already changed terminology and claims. “Epistemic Economics” became Economics of Epistemic Abundance; the “Law of Displaced Scarcity” became the Displaced Scarcity Hypothesis; the machine-discovery question is grounded in decades of computational and philosophical work; and the “effective adjacent possible” is explicitly attributed to existing innovation research.

Inspect the living intellectual lineage →

Portfolio discipline

Ideas can be abundant without active work becoming unbounded.

The programme uses a public Possibility Portfolio and a deliberately small Active Frontier. This is a local operating synthesis built from exploration/exploitation, innovation portfolio, real-options and idea-management literatures rather than a claim to new management theory.

Inspect the Active Frontier →

Frontier Expansion with Cognitive Tools

The meta-level question: how can human-machine systems improve the capacity to reach, recognize, validate and realize worthwhile possibilities?

Lineage / remaining question: Kauffman’s adjacent possible and Taalbi’s effective adjacent possible are direct antecedents. The remaining work is to understand which cognitive, epistemic and institutional capabilities actually enlarge the effective frontier and how to measure that without pretending to enumerate unknown possibilities.

active programme

Epistemic Stewardship & Handoff

The governance of claims and contributions when machine-assisted artefacts can outrun the initiator’s present capacity to defend them.

Lineage / remaining question: Builds on epistemic dependence, contributorship/guarantorship, metacognition, claim-accountability, knowledge-brokerage and absorptive-capacity traditions. The open question is how to operationalize claim-sensitive authority and handoff without creating new gatekeeping rituals.

active programme

Epistemic Uptake

The capacity of institutions to notice, route, evaluate, validate, integrate and realise candidate knowledge when idea generation becomes cheap.

Lineage / remaining question: Extends absorptive-capacity, transfer, brokerage, intermediary and expert-evaluation literatures into a regime of machine-generated candidate abundance. How should scarce expert attention be allocated?

active programme

Agalmic Economics

A contemporary programme about allocation and value around non-scarce or very low-marginal-cost goods and the scarce complements on which they still depend.

Lineage / remaining question: Robert Levin’s earlier agalmics is a direct antecedent. What does machine cognition change relative to that prior framing?

active programme

Economics of Epistemic Abundance

The allocation of scarce attention, validation, trust, institutional bandwidth and physical capability when candidate knowledge is unusually cheap to generate.

Lineage / remaining question: The name deliberately avoids claiming Grandori’s established “epistemic economics” territory. How do Simon’s attention scarcity, Weitzman’s processing constraint, absorptive capacity and modern AI-abundance economics interact?

active programme

Distributed Discovery & Provenance

The division of intellectual labour when humans and machines split problem framing, generation, significance recognition, validation, integration and realization.

Lineage / remaining question: Computational discovery and collective-centred AI discovery are established literatures. The remaining task is operational: represent novelty, priority, contribution and epistemic authority separately, then test whether the representation is useful.

active programme

Innovation Search Under AI

An AI-era extension of established evolutionary-economics, recombinant-search and adjacent-possible literatures.

Lineage / remaining question: How do lower search costs and larger branching factors change exploration, selection, testing, realization and the diversity of the search frontier? Which human capabilities remain complementary?

active programme

Attention & Selection

The economics and information theory of choosing among an expanding set of plausible ideas, models, artefacts and interventions.

Lineage / remaining question: Simon’s attention scarcity is foundational, and recent idea-evaluation work already identifies selection and expert-review bottlenecks. The new task is to model allocation under machine-amplified candidate production.

active programme

Representation as Discovery

Methods for finding representations that preserve useful structure while reducing cognitive, computational or physical cost.

Lineage / remaining question: EDA, visual analytics, information bottleneck and representation learning are antecedents. Novelty must be established at the level of concrete formalisms and evidence, including Moneta/Nemosyne.

active programme

Institutions, IP & Rents

Property, incentives and institutional design when invention, search and disclosure can happen at machine speed.

Lineage / remaining question: Builds on Arrow, appropriability/complementary-assets theory, open innovation and defensive-publication practice. What changes when search and candidate generation become dramatically cheaper?

active programme

Displaced Scarcity Hypothesis

When a previously binding constraint becomes sufficiently abundant, system performance and value become increasingly determined by complementary constraints that remain scarce.

The general intuition has strong antecedents in fixed-proportions bottlenecks, attention scarcity, complementary assets, weak-link/complementarity models and current AI-abundance economics. The hypothesis must earn usefulness through formal conditions, distinctive predictions and evidence.

Method

Reuse first. Differentiate second. Test third.

Each track should begin with an intellectual-lineage review, then state exactly what changes under the proposed machine-cognition regime. Formalism, experiments or software demonstrations follow only after the surviving contribution has been identified.

A literature result that collapses a supposed novelty claim is progress. A parked idea is not a failed idea. A published object should create useful capacity, not merely another unit of output.