6533b833fe1ef96bd129c3ae

RESEARCH PRODUCT

Learning for allocations in the long-run average core of dynamical cooperative TU games

Puduru Viswanadha ReddyDario Bauso

subject

Mathematical optimizationComputer scienceRobustness (computer science)Stochastic processBounded functionRule-based systemRobust controlVideo game designGame theoryMathematical economicsUpper and lower boundsgame theory control

description

We consider repeated coalitional TU games characterized by unknown but bounded and time-varying coalitions' values. We build upon the assumption that the Game Designer uses a vague measure of the extra reward that each coalition has received up to the current time to learn on how to re-adjust the allocations among the players. As main result, we present an allocation rule based on the extra reward variable that converges with probability one to the core of the long-run average game. Analogies with stochastic stability theory are put in evidence.

yearjournalcountryeditionlanguage
2011-02-01
10.1109/allerton.2010.5707043http://ieeexplore.ieee.org/Xplore/login.jsp?url=http://ieeexplore.ieee.org/iel5/5701578/5706874/05707043.pdf?arnumber=5707043&authDecision=-203