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Table 2 Actions performed in the case study.
Let us return to our initial normative question centered around (1) attitudes and (2) actions.
These claims can be seen as answers to the normative subset of our initial questions about (1) pro-national attitudes and (2) actions.
The basic reinforcement learning model consists of (1) environment states, (2) actions, (3) rules for transition between states, (4) immediate reward of transition rules, and (5) agent observation rules.
Participation is targeted through a methodology articulating: (1) structural analyses (organization of the discussions, regularity and involvement of participants, quotes-based social network) in usage-oriented and development-oriented mailing lists of the projects' discussion space; (2) actions to the code and documentation made by participants in the implementation and documentation spaces.
Thus, we have 256 possible decision rules (2 actions with 8 established observations).
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(4) Actions.
Another 102 actions are underway.
Figure 9 MEH of 7 actions.
A total of 63 actions were defined.
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CEO of Professional Science Editing for Scientists @ prosciediting.com