ArtificialLifeResearch
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Artificial Life Research
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Artificial Life research applies biological research results (see BiologicalLifeResearch) to aHuman unified mind model. Approach of implementing aHuman project is to reuse fundamental architecture of aHuman brain with all essential circuits and components. This page and its subpages define unified artificial mind model.
- see also alife topics at ArtificialLifeTopics
Contents
Implementation Approach
- Terms
- Target, targte sensor, target effector
- Regions type, implemented by specific class
- Region roles, connections
- Region connectors, sizing strategy, mapping strategy
- Sensory data in aHuman differ from classical AI:
- subsymbolic and scenic (e.g. aWee file sensor represents file as a point in scene, which makes it possible to see many files simultaneously and perceive file patterns)
- topological consistency, contingency and subjectivity (item projection to scene is reproduced in various patterns in the same view, view changes has consistent logic which allows to predict control efforts to make saccades)
- sensimotor interaction (sensor moves and data stream changes appropriately, aligned with controls)
Artificial Mind Overview
Biological mind can be modeled using set of cortices, nuclei, ganglia, glands and bundles of fibers:
- cortices and nuclei receive, process and relay information
- ganglia connect nuclei with muscles and glands, except for conscious motor connections which are direct from nuclei to muscles
- glands produce peptides to affect wide brain areas or hormones to affect body via blood system
- fibers connect brain components to each other
Bundles of fibers connecting different pairs of components are grouped in tracts:
- tracts can go in the same direction to a long distance
- fibers transfer fast signals as ion waves and mechanically transport molecular structures containing neurotransmitters and neuromodulators which affect connectivity between presynaptic and postsynaptic neurons
- various types of neurotransmitters and neuromodulators exert different influence on connectivity and signal relay from one neuron to another
- nuclei and fibers using specific neurotransmitter build global network which serves some generic function like motivation, inhibition or relaxation and so on
- when responding to specific stimuli, certain subsets of brain components behave as functional circuits with feedback and feedforward connections, which implements network firmly solving specific task in dynamic non-stationary environment
Artifical Mind is modeled using !MindArea, !MindRegion and link objects:
- MindArea is a group of mind components, defined by biological research.
- MindRegion is artificial representation of brain component of one of 3 types - cortex, nucleus or gland
- MindAreaLink corresponds to the tract and plays as signal transmission controller
- MindRegionLink represents bundle of fibers having specific properties of component-to-component mapping and also can be of different types depending on transmitter used
Formula of Artificial Life
- "human" =: "intelligent" "alive being"
- "intelligent" =: having "partially predefined" "complex memory"
- "partially predefined" =: "phyletic memory"
- "complex memory" =: having "specific structure" and "specific connectivity"
- "specific structure" =: "signal/noice logic", "holographic memory", "spatial and temporal memory"
- "specific connectivity" =: "two-way cortex memory", "memory processor circuit"
- "alive being" =: "broadly non-linear" "adaptive" "self"
- "broadly non-linear" =: "having great depth"
- "adaptive" =: "having environment-dependent behavior"
- "self" =: "embodied" "integrated circuits"
- "embodied" =: "having personal motivators"
- "integrated circuits" =: "hierarchically connected circuits"
- "intelligent" =: having "partially predefined" "complex memory"
Artificial Mind Areas
Artificial Mind Area | Functions | Biological Origins | Comments |
Area Regions
Area X
- text1
- text2
Functional Networks
Network Name | Role | Biological Origins | Comments |
Network X
- text1
- text2