Results 1 to 10 of about 5,279 (162)
An evolutionary game analysis of algorithmic indirect copyright infringement from the perspective of collusion between UGC platforms and direct infringers. [PDF]
PLoS ONEUser-generated content (UGC) is developing rapidly as an emerging platform form, however, the problem of indirect copyright infringement by algorithms is becoming more and more prominent, and infringement governance has become a key act in the ...
Jiangang Liu, Yuxuan Shen, Lanlan Zhou
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Eliminating single points of trust: a hybrid quantum and post-quantum blockchain with distributed key generation [PDF]
Scientific ReportsBlockchain systems built on classical cryptography face immediate risks from large-scale quantum computers, while purely quantum-based blockchains often rely on a single Private Key Generator (PKG) and incur heavy resource overheads.
Khang Wen Goh +5 more
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Algorithmic mechanisms for reliable crowdsourcing computation under collusion. [PDF]
PLoS ONE, 2015 We consider a computing system where a master processor assigns a task for execution to worker processors that may collude. We model the workers' decision of whether to comply (compute the task) or not (return a bogus result to save the computation cost)
Antonio Fernández Anta +3 more
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Algorithmic and Human Collusion [PDF]
SSRN Electronic Journal, 2021 As self-learning pricing algorithms become popular, there are growing concerns among academics and regulators that algorithms could learn to collude tacitly on non-competitive prices and thereby harm competition. I study popular reinforcement learning algorithms and show that they develop collusive behavior in a simulated market environment.
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European Papers, 2021 (Series Information) European Papers - A Journal on Law and Integration, 2021 6(2), 1193-1228 | Article | (Table of Contents) I. Preliminary remarks. - II. The increasing attractiveness of cartels in the age of big data analytics. - III.
Luca Calzolari
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Collusive Compensation Schemes Aided by Algorithms [PDF]
SSRN Electronic Journal, 2021 Sophisticated collusive compensation schemes such as assigning future market shares or direct transfers are frequently observed in detected cartels. We show formally why these schemes are useful for dampening deviation incentives when colluding firms are temporary asymmetric.
Martin, Simon, Schmal, W. Benedikt
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, 2022 This paper develops a formal framework to assess policies of learning algorithms in economic games. We investigate whether reinforcement-learning agents with collusive pricing policies can successfully extrapolate collusive behavior from training to the market. We find that in testing environments collusion consistently breaks down. Instead, we observe
Eschenbaum, Nicolas +2 more
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Autonomous algorithmic collusion: Q‐learning under sequential pricing [PDF]
The RAND Journal of Economics, 2021 AbstractPrices are increasingly set by algorithms. One concern is that intelligent algorithms may learn to collude on higher prices even in the absence of the kind of coordination necessary to establish an antitrust infringement. However, exactly how this may happen is an open question.
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Artificial Intelligence, Algorithmic Pricing, and Collusion [PDF]
American Economic Review, 2018 Increasingly, algorithms are supplanting human decision-makers in pricing goods and services. To analyze the possible consequences, we study experimentally the behavior of algorithms powered by Artificial Intelligence (Q-learning) in a workhorse oligopoly model of repeated price competition.
Calvano, Emilio +3 more
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Remedies for algorithmic tacit collusion
Journal of Antitrust Enforcement, 2020 Abstract There is growing evidence that tacit collusion can be autonomously achieved by machine learning technology, at least in some real-life examples identified in the literature and experimental settings. Although more work needs to be done to assess the competitive risks of widespread adoption of autonomous pricing agents, this is ...
Beneke, F., Mackenrodt, M.
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