Principle of Rationality

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Principle of Rationality

What is the principle of rationality?

The Principle of Rationality 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.

principle of rationality
Source: Lumen Learning

Karl R. Popper himself called his principle of rationality nearly empty (which means that it was devoid of emprical content) and strictly speaking false, but nonetheless tremendously useful. He got a large amount of criticism for saying these things because it made him look like he moved away from his famous Logic of Scientific Discovery.

Karl Popper wanted social science to be grounded in situational analysis. For that, it would be necessary to construct models of social situations which include individual actors and their relationship to social institutions, e.g. markets, legal codes, bureaucracies, etc. These modes would attribute specific aims and information to the actors. This would form the 'logic of the situation', the result of reconstructing meticulously all circumstances of an historical event. If you think about it, the principle of rationality is essentially the assumption that people are instrumental in attempting to achieve their goals and that is the factor that drives the model.


​​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”

What is Rational Choice Theory?

Rational choice theory is a theory in economics which states that individuals use their self-interests to make choices that will provide them with the greatest benefit. People weigh their options and make the choice they think will serve them best. It is a set of guidelines that assist in understanding economic and social behavior. 

The rational choice theory was put forth in the eighteenth century and goes all the way back to Adam Smith, who is considered to be the father of modern economics. This theory even suggests that a person’s self-driven rational actions will be beneficial for the overall economy. Rational choice theory looks at three concepts: rational actors, self interest and the invisible hand (which refers to unseen forces that drive the free market).

The way in which people make decisions regarding what will serve them in the best way is dependent on personal preferences. As an example, one person might decide to abstain from smoking because they want to take care of their health. But another person might decide to smoke because it helps them relieve their stress. These choices are the opposites of each other, but both the people make their decisions to get the best results according to their preferences.

Here are the assumptions of rational choice theory:

  • All actions are rational and are made by considering the costs and rewards.
  • The reward of a relationship or action needs to outweigh the cost for the action to be completed.
  • At the point when the value of the reward diminishes below the value of the costs incurred, the person will stop the action or end the relationship.
  • People will make use of the resources at their disposal to optimize their rewards.
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