Overview Index


What is an Action

Action is a process of acting or doing.

Examples of an Action:

  1. “Send a message over email”
  2. “Run the engine”.
  3. “Think about the Love”.
  4. “Save received information into external memory”.
  5. “Search for the way to achieve specified goal”.
  6. “Activate peripheral device XXX”.
  7. “Run Discover concept correlations routine”.
  8. Select information from the memory”.


How Strong AI selects an action to do

Scheduler and making decision routine define which action should be executed next.

The most probable candidate for the action is concept with the highest desirability value.

How action affects hardcoded unit behavior

Action is a concept which affects a hardcoded unit’s behavior.


“Run Programmator routine” is action which affects hardcoded unit behavior.


(The hardcoded unit affects the World state. Changes in the World state lead to events).


 “Take lunch” action causes:

  1. “Full stomach” event.
  2. “Empty wallet” event.


Thought and action

Thought results in action.


“I need good history knowledge” thought results in “Read a history book” action.



Strong AI considers every action as part of an experiment.

Event Correlation Analyzer searches for cause-effect relations between action and subsequent event.


“Read a history book” – is an action.

“Read a history book” is a cause concept for “good history knowledge” concept.

“Good history knowledge” is an effect concept for “Read a history book” action.

Event Correlation Analyzer reveals correlation between “Read a history book” and “good history knowledge’” and creates cause-effect relations “’Read a history book’->’ good history knowledge’”.


Action and the “Reward distribution routine”

Every action is evaluated by the reward distribution routine. As a result of such evaluation concepts responsible for the action are updated. In particular, desirability attributes of these concepts are updated (by reward value).


A man says “I love you” to a girl. The girl kisses the man. The man enjoys the kiss. That means that the man got a reward for “Saying ‘I love you’” action. Reward of the kiss is calculated accordaning to the man’s super goals (desire for tenderness, sexual instinct). The concepts / sub goals responsible for “Saying ‘I love you’” action is rewarded. The desirability attribute value of the concept is increased. “Saying ‘I love you’” action / sub goal becomes more desirable.


See also: