I propose to consider the question, 'Can machines think?'
This should begin with definitions of the meaning of the terms 'machine' and 'think'.
The definitions might be framed so as to reflect so far as possible the normal use of words,
but this attitude is dangerous.
If the meaning of the words 'machine' and 'think' are to be found
by examining how they are commonly used
it is difficult to escape the conclusion that the meaning
and the answer to the question, 'Can machines think?'
is to be sought in a statistical survey such as a Gallup poll. But this is absurd.
- A. M. Turing's (1950, p. 433) 'Computing Machinery and Intelligence'
The acting rationally approach is concerned with the underlying principles of rational behaviour
The acting rationally approach is supported by:
The Reinforcement Learning-Based Model of Interaction between an Agent and its Environment
The Rationality Assumption or Expected Utility Hypothesis
The Markov Decision Process
According to the Reinforcement Learning-Based Model of Interaction between an Agent and its Environment:
An agent is a minded entity that perceives through sensors (e.g. eyes, ears, cameras, etc), acts through effectors (e.g. hands, legs, motors, etc)
An agent also interacts with its environment and learns accordingly
At step t, the agent performs action At and receives observation Ot and the scalar reward Rt
The environment receives action At and emits observation Ot + 1 and the scalar reward Rt + 1