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Exploration-Exploitation in Multi-Agent Learning: Catastrophe Theory Meets Game Theory
Exploration-exploitation is a powerful and practical tool in multi-agent...
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Evolution of Coordination in Pairwise and Multi-player Interactions via Prior Commitments
Upon starting a collective endeavour, it is important to understand your...
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Mechanism Design and Blockchains
Game theory is often used as a tool to analyze decentralized systems and...
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Multi-Issue Bargaining With Deep Reinforcement Learning
Negotiation is a process where agents aim to work through disputes and m...
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Learning to Correlate in Multi-Player General-Sum Sequential Games
In the context of multi-player, general-sum games, there is an increasin...
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Option-critic in cooperative multi-agent systems
In this paper, we investigate learning temporal abstractions in cooperat...
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Catastrophe by Design in Population Games: Destabilizing Wasteful Locked-in Technologies
In multi-agent environments in which coordination is desirable, the history of play often causes lock-in at sub-optimal outcomes. Notoriously, technologies with a significant environmental footprint or high social cost persist despite the successful development of more environmentally friendly and/or socially efficient alternatives. The displacement of the status quo is hindered by entrenched economic interests and network effects. To exacerbate matters, the standard mechanism design approaches based on centralized authorities with the capacity to use preferential subsidies to effectively dictate system outcomes are not always applicable to modern decentralized economies. What other types of mechanisms are feasible? In this paper, we develop and analyze a mechanism that induces transitions from inefficient lock-ins to superior alternatives. This mechanism does not exogenously favor one option over another – instead, the phase transition emerges endogenously via a standard evolutionary learning model, Q-learning, where agents trade-off exploration and exploitation. Exerting the same transient influence to both the efficient and inefficient technologies encourages exploration and results in irreversible phase transitions and permanent stabilization of the efficient one. On a technical level, our work is based on bifurcation and catastrophe theory, a branch of mathematics that deals with changes in the number and stability properties of equilibria. Critically, our analysis is shown to be structurally robust to significant and even adversarially chosen perturbations to the parameters of both our game and our behavioral model.
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