How Much Would You Pay to Change a Game before Playing It?

Wolpert, David H.; Grana, Justin

doi:10.3390/e21070686

Cited by 3 publications

(3 citation statements)

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“…Envelop theorems assess changes of likely payoffs when a game is altered externally [14][15][16]. Wolpert and Grana [17] recently wondered how much an agent should pay if she (and no other actor involved) was given this control before playing a game. The decision boils down to a positive payoff balance with versus without intervention.…”

Section: Introductionmentioning

confidence: 99%

“…Different efforts might align or not, yielding uncertain returns. A single agent's decision to rig one game (as per [17]) might be of limited consequence in isolation. But effects may be amplified, mitigated, or produce emergent phenomena when coupled across games and players.…”

Section: Introductionmentioning

confidence: 99%

“…What is a natural level of intervention depending on these aspects? We could tackle these questions rigorously through utility functions that discount intervention costs, as in [17], extended to multiple agents and games; but this quickly becomes untreatable. Instead, inspired by agentbased models and complex adaptive systems [18][19][20][21][22][23], we capture essential elements that affect our research questions into a toy economy.…”

Section: Introductionmentioning

confidence: 99%

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Games in rigged economies

Seoane

2020

Preprint

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Modern economies evolved from simpler human exchanges into very convoluted systems. Today, a multitude of aspects can be regulated, tampered with, or left to chance; these are economic degrees of freedom which together shape the flow of wealth. Economic actors can exploit them, at a cost, and bend that flow in their favor. If intervention becomes widespread, microeconomic strategies of different actors can collide or resonate, building into macroeconomic effects. How viable is a 'rigged' economy, and how is this viability affected by growing economic complexity and wealth? Here we capture essential elements of 'rigged' economies with a toy model. Nash equilibria of payoff matrices in simple cases show how increased intervention turns economic degrees of freedom from minority into majority games through a dynamical phase. These stages are reproduced by agent-based simulations of our model, which allow us to explore scenarios out of reach for payoff matrices. Increasing economic complexity is then revealed as a mechanism that spontaneously defuses cartels or consensus situations. But excessive complexity enters abruptly into a regime of large fluctuations that threaten the system's viability. This regime results from non-competitive efforts to intervene the economy coupled across degrees of freedom, becoming unpredictable. Thus non-competitive actions can result in negative spillover due to sheer economic complexity. Simulations suggest that wealth must grow faster than linearly with economic complexity to avoid this regime and keep economies viable in the long run. Our work provides testable conclusions and phenomenological charts to guide policing of 'rigged' economic systems.

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