Bioinspiration

Use of biological principles to guide machine design; the paper calls for systematic rather than ad hoc bioinspiration

Neighborhood — ranked by edge-count

method

Evolutionary Algorithms
implements
Machine learning approach using evolutionary processes to generate and select designs, used to blur the designed vs. evolved distinction
Convolutional Neural Networks
implements
Biologically-inspired AI architecture cited as a successful example of bioinspiration from visual cortex organization
Deep Reinforcement Learning
implements
AI training method inspired by behaviorism, used for autonomous cars and drones; cited as bioinspired success

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.

Biological Softwareconcept0.747
The paper's characterization of living organisms' causal patterns as software — evolving, self-organizing, self-perpetuating, agentic — distinct from engineered code
Bioengineeringconcept0.744
Technology enabling creation of novel bodies and minds through rational construction, not only evolution.
Synthbiosisconcept0.726
Levin's proposed framework for mutually beneficial relationships between radically different intelligences.
Bioengineering of Synthetic Life Formsconcept0.724
Bioengineered and Synthetic Organismsconcept0.709
Biosemioticsconcept0.706
Framework treating meaning-making as intrinsic to living systems; supports view of memories as interpreted signs requiring creative interpretation.
Chimeric Bioengineeringconcept0.703
The creation of novel cognitive systems by combining evolved and designed components, driving the need for TAME.
Beaver Bioengineeringconcept0.702