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AUTONOMY & MEANING

Three Pillars of Intelligence: Control, Classification, Learning

Control	Is the ability to act with a purpose - affect the world in a way that has a target to be achieved. Anything from a thermostat controlling the temperature in a room to a human trying become rich and famous are examples of control systems. In the former case, measuring when the goal is achieved is easier than in the latter.
Classification	To act, one needs to know what to act on. To know what to act on, one needs to classify. To classify, one needs to sense. To sense, one needs measurement devices.
Learning	… is the accumulation of information for the purpose of control and classification. In a world that cannot be perceived all-at-once yet contains regularity, learning is necessary to conserve energy.

Control

Transducer	A device that changes one type of energy to another, typically amplifying and/or dampening the energy in the process.
Sensor	A transducer that changes one type of energy to another type.
Action	An effect that a controller can inflict on its external environment.
Actuator	A physical (or virtual/simulated) transduction mechanism that implements an action that a controller has committed to (e.g. gripper/hand).
Control Connection	Causal connection between a control signal and an actuator.
Adaptation	Modification of a control connection in light of a goal g that has not been achieved. Requires the control connection structure to change.
Digital Controller	Separates the stages of measurement, analysis, and control. Makes adaptive control in machines more feasible than a mechanical connection.
Feedback	For a variable v, information of its value at time t1 is transmitted back to the controller through a feedback mechanism as v', where v'(t) > v(t) that is, there is a latency in the transmission, which is a function of the speed of transmission (encoding (measurement) time + transmission time + decoding (read-back) time).
Latency	A measure for the size of the difference between v and v'.
Jitter	The change in Latency over time. Second-order latency.

Classification

ANNs	Contemporary ANNs (e.g. Deep Neural Networks, Double-Deep Q-Learners, etc.) can only do classification. They can only do classification by going through a long continuous training session, after which the learning is turned off.
Example of misguided use of classification	download video
Unified Control & Classification	To be an intelligent agent, classification must be unified with control and learning to produce am agent that can control its classification as turns out necessary to learn.

Learning


Learning to Classify	In a world with a lot of variation, a learning controller must also learn to classify. To learn to classify, one must learn what to control to classify appropriately. Learning to control, therefore, requires learning two kinds of classification (at the very least).

Meaning

Meaning	The meaning of a datum d to an agent A is defined by the effect that d has on the behavior of A.
More Specifically	Meaning is a mental state of an agent A that affects the control function of an autonomous agent. Given an agent A with a set of differentiable goals G, knowledge K, and a statement, S, the meaning of S is defined by how it selects between goals g in G, by preventing some and enabling other elements in G to be pursued.
Producing Meaning	Meaning is produced through a process of understanding using reasoning over causal relations.
Causal Relations	The relationship between two or more differentiable events such that one of them can (reasonably reliably) produce the other. One event E, the cause, must come before another event E', the effect, where E can (reasonably reliably) be used to produce E'.

Understanding

To consistently solve problems regarding a phenomenon <m>X</m> requires understanding <m>X</m>.
Understanding <m>X</m> means the ability to extract and analyze the meaning of any phenomena <m>\phi</m> related to <m>X</m>.

Bottom Line

Can't talk about creativity without talking about understanding, and can't talk about understanding without talking about meaning. No good scientific theory of meaning (but some philosophical ones) exists.

Autonomy

Center for Analysis and Design of Intelligent Agents

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