Causal emergence and artificial intelligence.pdf

TAGTAL LABS
Causal emergence and artificial intelligence
Machine Translated by Google
Shared by: Landon
Machine Translated by Google
Then there is artificial intelligence, symbolism (Graph), connectionism (ANN)
Wild intelligence is an ability, a kind of energy with strong generalization ability. Intelligent
energy can be seen behind abilities such as running, hunting, picking, making tools,
courtship, communication, etc., so it is called intelligence.
A simple understanding of artificial intelligence
Machine Translated by Google
If we can answer the above questions, can we also answer the circumstances under which new neurons and the links of new neurons are generated?
Under what circumstances will an aspect arise in software? Generate high-
scale networks?
Machine Translated by Google
SoC: Separation of Concerns "Separation of
Concerns" , even though it may not be perfect, is currently
the only available way to organize your thoughts.
Edsger W. Dijkstra
"On the Function of Scientific Thought"
"The design principle of all things"
Machine Translated by Google
Scattered in the system and difficult to encapsulate
Orthogonal concerns are
easy to encapsulate
cross-cutting concerns
Lacking methods and tools, is aspect-oriented programming the latest attempt? Learn from nature?
Functional programming, object-oriented programming
"Crosscutting Concerns"
Machine Translated by Google
Journal of Software: Evolution and Process · March 2016
Mario Luca Bernardi, Marta Cimitile and Giuseppe Di Lucca
Examples of cross-cutting concerns
Image source: Mining static and dynamic crosscutting concerns: A role-based approach
(Note how the green cross-cutting code validation is scattered across the various vertical modules)
Machine Translated by Google
Machine Translated by Google
Scattered in the system and difficult to encapsulate
Orthogonal concerns are
easy to encapsulate
cross-cutting concerns
Functional programming, object-oriented programming Lacking methods and tools, is aspect-oriented programming the latest attempt? Learn from nature?
There is a pain called "crosscutting concerns"
Machine Translated by Google
AOP Programming Paradiagram
Machine Translated by Google
Recent attempts: Aspect Oriented Programming encapsulates cross-
cutting concerns into programming semantics as Aspect
Machine Translated by Google
Aspect
object object
Machine Translated by Google
SoC: Separation of Concerns "Separation of
Concerns" , even though it may not be perfect, is currently
the only available way to organize your thoughts.
Edsger W. Dijkstra
"On the Function of Scientific Thought"
"The design principle of all things"
Machine Translated by Google
SoC: Separation of Concerns "Separation of
Concerns" , even though it may not be perfect, is currently
the only available way to organize your thoughts.
Edsger W. Dijkstra
"On the Function of Scientific Thought"
"The design principle of all things"
Machine Translated by Google
Movement, the basis of animal survival, requires the cooperation of all parts of the body and is a typical system
cross-cutting.
The cells differentiate into legs that allow the radiolarians to move in water with
limited movement. Corresponds to process-oriented programming.
The most primitive movement, single-cell radiolaria
How Nature Deals with Crosscutting Concerns—Movement
Machine Translated by Google
Cell shrinkage, object call
Communication between objects in object-oriented software is very similar to
primitive multicellular animals without nervous systems, such as sponges. Cells
communicate directly through gap junctions to produce simple movements. The
communicating cells must know the existence of each other (object name).
MuscleCell sponge_cell = new MuscleCell();
sponge_cell.contract();
TAGTAL LABS
Seawater is expelled through the contraction and relaxation of cells, and the
sponge floats in the seawater to obtain nutrients.
Machine Translated by Google
However, they are often clumsy, inflexible, and difficult to maintain.
TAGTAL LABS
Various forms of glass sponges
"Original" OO can also build complex systems
Machine Translated by Google
Nerve cells generate more complex movements to 'prey'
http://musculuscomplexio.weebly.com/hydra-oligactis.html
Leech's mouthparts create complex movements to capture single-celled microorganisms
"Transverse" nervous systems first appeared in coelenterates (such as leeches).
Neurons are partially separated from the potentiators (muscle cells) and form a nerve
center-less neural network through which neural signals are broadcast throughout the
body to stimulate all muscle cells to produce simple, slow predatory movements.
TAGTAL LABS
Machine Translated by Google
Redundant system, and difficult to produce complex movements. The occurrence of new motor
organs also requires more complex motor control. The central nervous system of vertebrates,
Aspect of Aspect
TAGTAL LABS
Earthworms create complex movements using reusable components
Machine Translated by Google
Each earthworm body segment contains the "code" for how to
produce movement by alternating actions of longitudinal and
circular muscles - the ganglion, a "single-purpose" aspect.
TAGTAL LABS
https://upload.wikimedia.org/wikipedia/commons/e/ea/Annelid_redone_w_white_background.svg
Reusable motion components—body segments
Machine Translated by Google
Movement (running, flying)
Neuronal “encapsulation” of cross-cutting concerns
Machine Translated by Google
Aspect
object object
Analogy: Nerve + Muscle vs Aspect + Object
VS
TAGTAL LABS
Both Neuron and Aspect are "encapsulation" of cross-cutting concerns.
Machine Translated by Google
Advice
Anatomical Analogy between Aspect and Neuron
PointCut
join point
Synapse
(join point)
Aspect
Machine Translated by Google
Networks and
Paradigm
Metaphor
between Neural
Aspect_Oriented
Programming
Machine Translated by Google
Advice
axon
point of contact between synaptic axon and target cell
Point Cut
Code points where aspect intersects with the target
object
Signal Transduction
Code point context acquisition mechanism for target
objects
join
point
Code snippets, injected at the join point and run
in the context of the target object, can change the
running state of the object.
Components that connect neurons to target
cells
Signal transduction is the process by which
chemical or physical signals are transmitted
through cells as a series of molecular events,
ultimately causing a cellular response.
Neurons Aspect
Machine Translated by Google
Advice, which is similar to neuron signal transduction logic, is the logic to implement
cross-cutting. It can change the behavior of the target object synapsed by its own
PointCut's connection point, and can be activated by the connection point. The
activated Advice performs certain operations, such as before(), around(), and
after(), in the context of the join point to achieve crosscutting. Advice is not accessible
to any object. In other words, the object cannot call the operation of Advice, thus
ensuring cross-cutting modularity.
Advice vs Transduction
Machine Translated by Google
Aspects can pass information from target to target. We call it PointCut, which transfers
information from the target to the aspect where it belongs, similar to the dendrites of a neuron.
PointCut together with join point adds a new communication mechanism similar to synaptic
communication in the OO paradigm. PointCut is the main execution unit of Aspect and is
able to obtain the context of the target object synapsed by its own connection point (we
also call it the context of the connection point). A PointCut connected to at least one Advice
can have multiple connection points, which are program execution points similar to cell
membrane receptors defined in an object or aspect. It can be a method call, method
execution, etc., through which PointCut synapses with an object or aspect. In contrast, the
direction of impulse transmission in the axon of most neurons is always from the base of
the axon to its terminal, the information in PointCut is transmitted directly in both directions, i.e.
Point Cut vs AXON
Machine Translated by Google
In order to meet the needs of survival, animals have developed more complex
modes of movement through evolution, such as jetting, swimming, crawling,
running, flying, jumping, walking...
Complex behaviors are not accomplished by direct communication between muscle cells, but by centralized
control by nerve centers. Obviously, this method can reduce the complexity of the animal. Otherwise, for example,
every muscle cell on the body segment must have the same "movement logic". We could say that nature has
encapsulated "crosscutting" into ganglia (neurons). This phenomenon is more common in vertebrates (Fig. 1).
The extreme example is the cortex, where the most complex "crosscuttings" such as emotions and learning
abilities are well processed.
Aspect of AspectThe depth of the hierarchy
Machine Translated by Google
e
A spec
t
joint point
object
PointCut
Advic
Biological nervous system morphological calculation simulation implemented using AOP (AspectJ)
Machine Translated by Google
The sensory neuron in neuronal network is
implemented as an aspect whichhas two pointcuts ,
axon() and dendrite(), similar to that of neuron.
Machine Translated by Google
MotorNeuron is an aspect similar to SensoryNeuron. However there are
two differences between SensoryNeuron and MotorNeuron.
Machine Translated by Google
If we can answer the above questions, can we also answer the circumstances under which new neurons and the links between new neurons are generated?
Under what circumstances will an aspect arise in software? Generate high-
scale networks?
Machine Translated by Google
The transfer probability is recorded as
reflected on the Internet
Noise level.
Represents possible transitions and their probabilities in the causal structure network, transitions between nodes
The average value of Shannon entropy on all nodes represents the causal structure of the network.
(normalized according to the total weight of the network), its Shannon entropy
Effective information = Shannon entropy of causal structured
network - mean value of Shannon entropy of each node
The vector contains the sum of each node's incoming weights from its previous neighbor.
a definite distribution. If all nodes are linked to the same node then
causal emergence
Machine Translated by Google
Machine Translated by Google
Machine Translated by Google
A
D
E
C
B
0,33
0,5
0,5
0,5
1.0
0,5
0,33
0.2*2.32192809489
0,5
0,5
0,33
Machine Translated by Google
1.736965
1.378?
0.58568
0.9995
Machine Translated by Google
EI of common networks and their properties
Machine Translated by Google
Machine Translated by Google
It may be surprising that evolving networks are so inefficient. However,
as we will show, inefficiency can actually indicate the presence of
informative (macro) dependencies in the system. That is, the low
efficiency may reflect the fact that biological systems often contain
higher-scale causal structures, as we will demonstrate in the next section.
Machine Translated by Google
causal reduction
micro node
high-level network
macro node
causal structure
causal emergence
Examples of causal emergence
Machine Translated by Google
Causal emergence occurs when a reorganized network GM (macro scale) has more
effective information EI than the original network G (micro scale). In general, less
efficient networks (EIs that are smaller relative to their network size) are more likely to
emerge because these networks can be remapped to reduce their uncertainty.
Searching the space of possible recombination ways can identify or approximate the
macroscopic network scale that maximizes EI.
Macro nodes may be in the same network as micro nodes. Existing methods for
searching network mapping that maximize EI: two-node combination method (three-
node combination is too computationally expensive), greedy search (local optimal solution)
Machine Translated by Google
object object
Aspect
Aspect causally emerges from objects
Machine Translated by Google
Machine Translated by Google
Machine Translated by Google
Walking: Example of implementing cross-cutting
Machine Translated by Google
Machine Translated by Google
Machine Translated by Google
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Causal emergence and artificial intelligence.pdf

  • 1. TAGTAL LABS Causal emergence and artificial intelligence Machine Translated by Google
  • 2. Shared by: Landon Machine Translated by Google
  • 3. Then there is artificial intelligence, symbolism (Graph), connectionism (ANN) Wild intelligence is an ability, a kind of energy with strong generalization ability. Intelligent energy can be seen behind abilities such as running, hunting, picking, making tools, courtship, communication, etc., so it is called intelligence. A simple understanding of artificial intelligence Machine Translated by Google
  • 4. If we can answer the above questions, can we also answer the circumstances under which new neurons and the links of new neurons are generated? Under what circumstances will an aspect arise in software? Generate high- scale networks? Machine Translated by Google
  • 5. SoC: Separation of Concerns "Separation of Concerns" , even though it may not be perfect, is currently the only available way to organize your thoughts. Edsger W. Dijkstra "On the Function of Scientific Thought" "The design principle of all things" Machine Translated by Google
  • 6. Scattered in the system and difficult to encapsulate Orthogonal concerns are easy to encapsulate cross-cutting concerns Lacking methods and tools, is aspect-oriented programming the latest attempt? Learn from nature? Functional programming, object-oriented programming "Crosscutting Concerns" Machine Translated by Google
  • 7. Journal of Software: Evolution and Process · March 2016 Mario Luca Bernardi, Marta Cimitile and Giuseppe Di Lucca Examples of cross-cutting concerns Image source: Mining static and dynamic crosscutting concerns: A role-based approach (Note how the green cross-cutting code validation is scattered across the various vertical modules) Machine Translated by Google
  • 9. Scattered in the system and difficult to encapsulate Orthogonal concerns are easy to encapsulate cross-cutting concerns Functional programming, object-oriented programming Lacking methods and tools, is aspect-oriented programming the latest attempt? Learn from nature? There is a pain called "crosscutting concerns" Machine Translated by Google
  • 10. AOP Programming Paradiagram Machine Translated by Google
  • 11. Recent attempts: Aspect Oriented Programming encapsulates cross- cutting concerns into programming semantics as Aspect Machine Translated by Google
  • 13. SoC: Separation of Concerns "Separation of Concerns" , even though it may not be perfect, is currently the only available way to organize your thoughts. Edsger W. Dijkstra "On the Function of Scientific Thought" "The design principle of all things" Machine Translated by Google
  • 14. SoC: Separation of Concerns "Separation of Concerns" , even though it may not be perfect, is currently the only available way to organize your thoughts. Edsger W. Dijkstra "On the Function of Scientific Thought" "The design principle of all things" Machine Translated by Google
  • 15. Movement, the basis of animal survival, requires the cooperation of all parts of the body and is a typical system cross-cutting. The cells differentiate into legs that allow the radiolarians to move in water with limited movement. Corresponds to process-oriented programming. The most primitive movement, single-cell radiolaria How Nature Deals with Crosscutting Concerns—Movement Machine Translated by Google
  • 16. Cell shrinkage, object call Communication between objects in object-oriented software is very similar to primitive multicellular animals without nervous systems, such as sponges. Cells communicate directly through gap junctions to produce simple movements. The communicating cells must know the existence of each other (object name). MuscleCell sponge_cell = new MuscleCell(); sponge_cell.contract(); TAGTAL LABS Seawater is expelled through the contraction and relaxation of cells, and the sponge floats in the seawater to obtain nutrients. Machine Translated by Google
  • 17. However, they are often clumsy, inflexible, and difficult to maintain. TAGTAL LABS Various forms of glass sponges "Original" OO can also build complex systems Machine Translated by Google
  • 18. Nerve cells generate more complex movements to 'prey' http://musculuscomplexio.weebly.com/hydra-oligactis.html Leech's mouthparts create complex movements to capture single-celled microorganisms "Transverse" nervous systems first appeared in coelenterates (such as leeches). Neurons are partially separated from the potentiators (muscle cells) and form a nerve center-less neural network through which neural signals are broadcast throughout the body to stimulate all muscle cells to produce simple, slow predatory movements. TAGTAL LABS Machine Translated by Google
  • 19. Redundant system, and difficult to produce complex movements. The occurrence of new motor organs also requires more complex motor control. The central nervous system of vertebrates, Aspect of Aspect TAGTAL LABS Earthworms create complex movements using reusable components Machine Translated by Google
  • 20. Each earthworm body segment contains the "code" for how to produce movement by alternating actions of longitudinal and circular muscles - the ganglion, a "single-purpose" aspect. TAGTAL LABS https://upload.wikimedia.org/wikipedia/commons/e/ea/Annelid_redone_w_white_background.svg Reusable motion components—body segments Machine Translated by Google
  • 21. Movement (running, flying) Neuronal “encapsulation” of cross-cutting concerns Machine Translated by Google
  • 22. Aspect object object Analogy: Nerve + Muscle vs Aspect + Object VS TAGTAL LABS Both Neuron and Aspect are "encapsulation" of cross-cutting concerns. Machine Translated by Google
  • 23. Advice Anatomical Analogy between Aspect and Neuron PointCut join point Synapse (join point) Aspect Machine Translated by Google
  • 25. Advice axon point of contact between synaptic axon and target cell Point Cut Code points where aspect intersects with the target object Signal Transduction Code point context acquisition mechanism for target objects join point Code snippets, injected at the join point and run in the context of the target object, can change the running state of the object. Components that connect neurons to target cells Signal transduction is the process by which chemical or physical signals are transmitted through cells as a series of molecular events, ultimately causing a cellular response. Neurons Aspect Machine Translated by Google
  • 26. Advice, which is similar to neuron signal transduction logic, is the logic to implement cross-cutting. It can change the behavior of the target object synapsed by its own PointCut's connection point, and can be activated by the connection point. The activated Advice performs certain operations, such as before(), around(), and after(), in the context of the join point to achieve crosscutting. Advice is not accessible to any object. In other words, the object cannot call the operation of Advice, thus ensuring cross-cutting modularity. Advice vs Transduction Machine Translated by Google
  • 27. Aspects can pass information from target to target. We call it PointCut, which transfers information from the target to the aspect where it belongs, similar to the dendrites of a neuron. PointCut together with join point adds a new communication mechanism similar to synaptic communication in the OO paradigm. PointCut is the main execution unit of Aspect and is able to obtain the context of the target object synapsed by its own connection point (we also call it the context of the connection point). A PointCut connected to at least one Advice can have multiple connection points, which are program execution points similar to cell membrane receptors defined in an object or aspect. It can be a method call, method execution, etc., through which PointCut synapses with an object or aspect. In contrast, the direction of impulse transmission in the axon of most neurons is always from the base of the axon to its terminal, the information in PointCut is transmitted directly in both directions, i.e. Point Cut vs AXON Machine Translated by Google
  • 28. In order to meet the needs of survival, animals have developed more complex modes of movement through evolution, such as jetting, swimming, crawling, running, flying, jumping, walking... Complex behaviors are not accomplished by direct communication between muscle cells, but by centralized control by nerve centers. Obviously, this method can reduce the complexity of the animal. Otherwise, for example, every muscle cell on the body segment must have the same "movement logic". We could say that nature has encapsulated "crosscutting" into ganglia (neurons). This phenomenon is more common in vertebrates (Fig. 1). The extreme example is the cortex, where the most complex "crosscuttings" such as emotions and learning abilities are well processed. Aspect of AspectThe depth of the hierarchy Machine Translated by Google
  • 29. e A spec t joint point object PointCut Advic Biological nervous system morphological calculation simulation implemented using AOP (AspectJ) Machine Translated by Google
  • 30. The sensory neuron in neuronal network is implemented as an aspect whichhas two pointcuts , axon() and dendrite(), similar to that of neuron. Machine Translated by Google
  • 31. MotorNeuron is an aspect similar to SensoryNeuron. However there are two differences between SensoryNeuron and MotorNeuron. Machine Translated by Google
  • 32. If we can answer the above questions, can we also answer the circumstances under which new neurons and the links between new neurons are generated? Under what circumstances will an aspect arise in software? Generate high- scale networks? Machine Translated by Google
  • 33. The transfer probability is recorded as reflected on the Internet Noise level. Represents possible transitions and their probabilities in the causal structure network, transitions between nodes The average value of Shannon entropy on all nodes represents the causal structure of the network. (normalized according to the total weight of the network), its Shannon entropy Effective information = Shannon entropy of causal structured network - mean value of Shannon entropy of each node The vector contains the sum of each node's incoming weights from its previous neighbor. a definite distribution. If all nodes are linked to the same node then causal emergence Machine Translated by Google
  • 38. EI of common networks and their properties Machine Translated by Google
  • 40. It may be surprising that evolving networks are so inefficient. However, as we will show, inefficiency can actually indicate the presence of informative (macro) dependencies in the system. That is, the low efficiency may reflect the fact that biological systems often contain higher-scale causal structures, as we will demonstrate in the next section. Machine Translated by Google
  • 41. causal reduction micro node high-level network macro node causal structure causal emergence Examples of causal emergence Machine Translated by Google
  • 42. Causal emergence occurs when a reorganized network GM (macro scale) has more effective information EI than the original network G (micro scale). In general, less efficient networks (EIs that are smaller relative to their network size) are more likely to emerge because these networks can be remapped to reduce their uncertainty. Searching the space of possible recombination ways can identify or approximate the macroscopic network scale that maximizes EI. Macro nodes may be in the same network as micro nodes. Existing methods for searching network mapping that maximize EI: two-node combination method (three- node combination is too computationally expensive), greedy search (local optimal solution) Machine Translated by Google
  • 43. object object Aspect Aspect causally emerges from objects Machine Translated by Google
  • 46. Walking: Example of implementing cross-cutting Machine Translated by Google