Incentive Games and Mechanisms for Risk Management

Computer Science – Computer Science and Game Theory

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

Scientific paper

Incentives play an important role in (security and IT) risk management of a large-scale organization with multiple autonomous divisions. This paper presents an incentive mechanism design framework for risk management based on a game-theoretic approach. The risk manager acts as a mechanism designer providing rules and incentive factors such as assistance or subsidies to divisions or units, which are modeled as selfish players of a strategic (noncooperative) game. Based on this model, incentive mechanisms with various objectives are developed that satisfy efficiency, preference-compatibility, and strategy-proofness criteria. In addition, iterative and distributed algorithms are presented, which can be implemented under information limitations such as the risk manager not knowing the individual units' preferences. An example scenario illustrates the framework and results numerically. The incentive mechanism design approach presented is useful for not only deriving guidelines but also developing computer-assistance systems for large-scale risk management.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Incentive Games and Mechanisms for Risk Management does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Incentive Games and Mechanisms for Risk Management, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Incentive Games and Mechanisms for Risk Management will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-13698

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.