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Principle of Rationality

What is the Principle of Rationality?

The Principle of Rationality is also known as the Rationality Principle. It was coined by Karl R. Popper in a lecture that he delivered at Harvard in 1963. It was later published in his book Myth of Framework. The principle is related to the ‘logic of the situation’, which he referred to in his Economica article, and further wrote about in his book, ‘The Poverty of Historicism’.

It suggests that agents act in the most appropriate manner depending on the objective situation. The principle essentially is an idealized conception of human behavior which helped Karl in driving his model of situational analysis.

Rationality, essentially, is a property of action. It does not clearly specify or define the process through which actions are selected, but it constrains it.


​​What are the characteristics of a rational agent in artificial intelligence?

Rationally agents are agents whose actions are logical with regard to the information (or situation) processed by the agent and its goals (or the purpose for which the agent was designed).

Such agents have clear preferences, they model uncertainty, and they tend to act in a manner that would maximize their performance measure with all possible actions.

Artificial intelligence focuses on the creation of rational agents to be used in game theory and decision theory for a wide range of real-world situations.

Rational action is extremely important for an AI agent because in reinforcement learning algorithms, agents get a reward for performing the best possible action, but they get a penalty for performing the wrong action.

Here are the points on the basis of which rationality is judged:

  • The existence of a performance measure that defines the success criterion.
  • The agent having prior knowledge about its environment.
  • The best possible actions for an agent to perform.
  • The sequence of percepts


What is Perfect Rationality?

Perfect rationality refers to the ability to generate or choose behavior that will bring maximum success, given the situation and available information.

It constrains the ability of an agent to provide the maximum expectation of success while considering the information that is available. 

The knowledge-level analysis of artificial intelligence systems is dependent on the assumption of perfect rationality. 

It is used to establish an upper bound on the performance of a system, by understanding and establishing the actions that a perfectly rational agent would do in an identical situation, with the same knowledge available. 


What is Calculative Rationality?

Calculative rationality is the capacity to compute a perfectly rational decision with the information initially available. 

This type of rationality is exhibited by agent programs that would result in perfectly rational behavior if the program was executed infinitely fast.

Endeavoring for calculative rationality has been the main activity of theoretically well-founded research in artificial intelligence.


What is Metalevel Rationality?

Metalevel rationality is also referred to as Type II rationality. It is the ability to pick an optimal combination of computation-sequence-plus-action, under the constraint that the action needs to be picked by the computation. 

It is based on the idea of identifying the optimal balance between computational costs and decision quality. 

I.J. Good defined Type II rationality as, 

“the maximization of expected utility taking into account deliberation costs”

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Principle of Rationality

October 14, 2020

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What is the Principle of Rationality?

The Principle of Rationality is also known as the Rationality Principle. It was coined by Karl R. Popper in a lecture that he delivered at Harvard in 1963. It was later published in his book Myth of Framework. The principle is related to the ‘logic of the situation’, which he referred to in his Economica article, and further wrote about in his book, ‘The Poverty of Historicism’.

It suggests that agents act in the most appropriate manner depending on the objective situation. The principle essentially is an idealized conception of human behavior which helped Karl in driving his model of situational analysis.

Rationality, essentially, is a property of action. It does not clearly specify or define the process through which actions are selected, but it constrains it.


​​What are the characteristics of a rational agent in artificial intelligence?

Rationally agents are agents whose actions are logical with regard to the information (or situation) processed by the agent and its goals (or the purpose for which the agent was designed).

Such agents have clear preferences, they model uncertainty, and they tend to act in a manner that would maximize their performance measure with all possible actions.

Artificial intelligence focuses on the creation of rational agents to be used in game theory and decision theory for a wide range of real-world situations.

Rational action is extremely important for an AI agent because in reinforcement learning algorithms, agents get a reward for performing the best possible action, but they get a penalty for performing the wrong action.

Here are the points on the basis of which rationality is judged:

  • The existence of a performance measure that defines the success criterion.
  • The agent having prior knowledge about its environment.
  • The best possible actions for an agent to perform.
  • The sequence of percepts


What is Perfect Rationality?

Perfect rationality refers to the ability to generate or choose behavior that will bring maximum success, given the situation and available information.

It constrains the ability of an agent to provide the maximum expectation of success while considering the information that is available. 

The knowledge-level analysis of artificial intelligence systems is dependent on the assumption of perfect rationality. 

It is used to establish an upper bound on the performance of a system, by understanding and establishing the actions that a perfectly rational agent would do in an identical situation, with the same knowledge available. 


What is Calculative Rationality?

Calculative rationality is the capacity to compute a perfectly rational decision with the information initially available. 

This type of rationality is exhibited by agent programs that would result in perfectly rational behavior if the program was executed infinitely fast.

Endeavoring for calculative rationality has been the main activity of theoretically well-founded research in artificial intelligence.


What is Metalevel Rationality?

Metalevel rationality is also referred to as Type II rationality. It is the ability to pick an optimal combination of computation-sequence-plus-action, under the constraint that the action needs to be picked by the computation. 

It is based on the idea of identifying the optimal balance between computational costs and decision quality. 

I.J. Good defined Type II rationality as, 

“the maximization of expected utility taking into account deliberation costs”

Thanks for reading! We hope you found this helpful.

Ready to level-up your business? Click here.

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