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Towards Optimal Control of Evolutionary Games on Networks

Riehl, J. R. & Cao, M., 3-Jan-2017, In : IEEE Transactions on Automatic Control. 62, 1, p. 458-462

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We investigate the control of evolutionary games on networks, in which each edge represents a two-player repeating game between neighboring agents. After
each round of games, agents can update their strategies based on local payoff and strategy information, while a subset of agents can be assigned strategies and thus serve as control inputs. We seek here the smallest set of control agents needed to drive the network to a desired uniform strategy state. After presenting exact solutions for complete and star networks and describing a general solution approach that is computationally practical only for small networks, we design a fast algorithm for approximating the solution on arbitrary networks using a weighted minimum spanning tree and strategy propagation algorithm.We show
that the resulting approximation is exact for certain classes of games on complete and star networks. Finally, simulations demonstrate that the algorithm yields near-optimal solutions in more general cases, although it performs best
for coordination games.
Original languageEnglish
Pages (from-to)458-462
JournalIEEE Transactions on Automatic Control
Volume62
Issue number1
Publication statusPublished - 3-Jan-2017

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