Game Theory seminars

Multi-agent reinforcement learning (MARL) has recently shown great promise as an approach to networked system control. Arguably, one of the most difficult and important tasks for which large scale networked system control is applicable is common-pool resource (CPR) management. Crucial CPRs include arable land, fresh water, wetlands, wildlife, fish stock, forests and the atmosphere, of which proper management is related to some of society’s greatest challenges such as food security, inequality and climate change. This talk will consist of three parts. In the first, we will briefly look at climate change and how it poses a significant threat to life on our planet. In the second, we will consider the potential of multi-agent systems for climate change mitigation and adaptation. And finally, in the third, we will discuss recent research from InstaDeep into better understanding the behaviour of networked MARL systems used for CPR management. More specifically, we will see how the tools from empirical game-theoretic analysis may be harnessed to analyse the differences in networked MARL systems. The results give new insights into the consequences associated with certain design choices and provide an additional dimension of comparison between systems beyond efficiency, robustness, scalability and mean control performance.

Aram Harrow connects the Unique Games conjecture, especially small-set expansion, with the quantum separability problem. The Lasserre hierarchy used for Unique Games and the k-extendible relaxation of quantum separability turn out to be closely equivalent algorithmic approaches. The talk examines how quantum-information conjectures could yield quasipolynomial algorithms or hardness results for Unique Games, and discusses promising research directions. It introduces the necessary quantum mechanics, Unique Games, and hierarchy background rather than presupposing it. The presentation draws partly on the papers arXiv:1205.4484 and arXiv:1210.6367.