Abstract intelligence and cognitive robots
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Abstract intelligence is the human enquiry of both natural and artificial intelligence at the neural, cognitive, functional, and logical levels reductively from the bottom up. According to the abstract intelligence theory, a cognitive robot is an autonomous robot that is capable of thought, perception, and learning based on the three-level computational intelligence known as the imperative, autonomic, and cognitive intelligence. This paper presents the theoretical foundations of cognitive robots based on the latest advances in abstract intelligence, cognitive informatics, and denotational mathematics. A formal model of intelligence known as the Generic Abstract Intelligence Mode (GAIM) is developed, which provides a foundation to explain the mechanisms of advanced natural intelligence such as thinking, learning, and inference. A set of denotational mathematics is introduced for rigorously modeling and manipulating the behaviors of cognitive robots. A case study on applications of a denotational mathematics, visual semantic algebra (VSA), is presented in architectural and behavioral modeling of cognitive robots based on the theory of abstract intelligence.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it