Automated Incentive Management for Social Computing - Foundations, Models, Tools and Algorithms

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amount of time, but at least until the moment of the application of the action is called the effectiveness range. possible effectiveness range

possible evaluation range

t

announced

applied

Figure 3.2: Application and effectiveness of rewarding actions.

3.3.3

Incentive Conditions

Incentive conditions state precisely how, when, and where to apply rewarding actions. Each consists of at most three components (subconditions):

• Parameter component expresses a subcondition in form of a logical formula over a specified number of parameters that describe an agent. For example: such a condition could filter out all the agents whose productivity is less than the team’s average. • Time component is used to formulate a condition over past behavior of an agent. For example: select all the agents who within last three months had an unsatisfactory productivity level. • Structure component filters out agents based on the relations they take part in. This component can be used to select members of a team, or all the collaborators of a specific agent.

By using all three components at the same time we can specify a complex condition, e.g.: “incentivize the subordinates of a specific manager, who over the last year achieved a score higher than 60% in at least 10 months.” Incentive conditions are part of the business logic, and as such are stipulated by the domain experts empowered by the principal to manage the workforce. However, a small organization can take an advantage of some good practices and employ pre-made incentive models (patterns) adapted to fit particular organization’s needs. Feedback information obtained through monitoring execution of rewarding actions can be used to adapt condition parameters. 34


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