There is no concrete For autonomous sensorimotor systems like us, all objects, whether primroses or prime numbers, are abstractions

What autonomous systems can do see (sense, perceive, “discriminate relatively”) learn recognize (categorize kinds and individuals, “discriminate absolutely”)) manipulate (Manipulate) name (identify) describe

Abstraction Detecting invariants in variance Features/parts/relations Sensorimotor interactions Gibsonian “affordances”

Foundations of Abstraction Borges’s Funes the Memorious Lurias’s “S”: The Mind of a Mnemonist Watanabe’s “Ugly Dckling Theorem” Miller’s “Magical Number 7 +/- 2”

Discrimination Relative Discrimination: same/different judgments, analog matching, similarity judgment, more/less magnitude judgment, Just-Noticeable-Differences (JNDs) Absolute Discrimination: (recognition, identification, sorting/labeling, naming)

Informational capacity limits Relative discrimination: JNDs Absolute discrimination: “chunks” Serial memory limits Rechunking Recoding Invariance extraction

Categorical perception Implicit/Explicit learning/knowledge Chicken-sexing Biederman’s “geon” analysis

3 ways of getting categories Darwinian “theft” (innately prepared feature detectors Sensorimotor “toil” (trial and error learning of categories from experience, with error- corrective feedback, “knowledge by acquaintance”) Symbolic “theft” (learning from “hearsay”: “knowledge by description,” language)

How do autonomous systems access objects? Through category detection All category detection depends on abstraction: selectivity, invariance extraction Objects are whatever affords absolute discriminability, whether kinds or individuals, from primroses to prime numbers