Algorithmic Game Theory

By M. Serna. Lecture Notes in Computer Science, 2012

3,487 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Computer Networks and Communications, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/ee10876c3f61ce18aa7f663c898360f2547245a8

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Citations in the corpus

Decentralized Anti-coordination Through Multi-agent Learning (2013, methodology): “Blum and Mansour (2007) present a general technique to convert any learning algorithm with low external regret to an algorithm with a low internal regret. The idea is to run multiple copies of the external regret algorithm. In each step, each copy returns a probability vector of playing each action.”
How to Train Your DRAGAN (2017, methodology): “In this paper, we introduce regret-minimization (RM) [7, 6] as a technique to reach Nash Equilibrium in games.”
TRAC: Truthful auction for location-aware collaborative sensing in mobile crowdsourcing (2014, background): “This essentially rule out the possibility of exploiting the traditionally VCG mechanism [13] for our problem.”
On Finding Local Nash Equilibria (and Only Local Nash Equilibria) in Zero-Sum Games (2019, neutral): “The classical problem of ﬁnding Nash equilibria in multi-player games has been a focus of intense research in computer science, control theory, economics and mathematics (Basar and Olsder, 1998; Nisan et al., 2007; C. Daskalakis, 2009).”
Competitive Gradient Descent (2019, background): “The beneﬁts of competition: While competitive optimization problems arise naturally in mathematical economics and game/decision theory (Nisan et al., 2007), they also provide a highly expressive and transparent language to formulate algorithms in a wide range of domains.”
Higher-Order Approximate Relational Refinement Types for Mechanism Design and Differential Privacy (2014, background): “Mechanism Design Mechanism design was introduced to the theoretical computer science community (with a new focus on efﬁcient implementations) by the seminal work of Nisan and Ronen [41] (See Nisan et al. [42] for a textbook introduction).”
Revenue generation for truthful spectrum auction in dynamic spectrum access (2009, background): “The requirement of satisfying the interference constraints is not present in existing literatures of auction design [13].”
Decentralized Learning in Online Queuing Systems (2021, background): “Many related results are known in the classical repeated games [see e.g., Cesa-Bianchi and Lugosi, 2006, Roughgarden, 2010], where a single game is repeated over independent rounds (but the agents strategies might evolve and depend on the history).”
Forecasting Interactive Dynamics of Pedestrians with Fictitious Play (2016, background): “It has been applied to a range of disciplines including economic theory [31], politics [7] and computer science [28].”