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In this paper, we consider a simple two-player attack and defense model, focusing on the role of players' abilities and choice timing. Abilities are divided into skills and efficiency, where the former is an absolute notion and the latter a relative notion of ability. Timing is investigated by comparing players' investments in a simultaneous and a Stackelberg game. In the simultaneous game, the Nash Equilibrium investment level in attack and defense resources is symmetric, increasing in the skills but non-monotonic in the relative efficiency. In the Stackelberg game, the equilibrium investment levels are asymmetric, increasing in the skills, but with their ranking affected only by the relative efficiency. Therefore, interestingly, players' choice is mostly characterized by players' relative efficiency rather than by their skills, in regards to timing.

Confirmation of Bitcoin transactions is executed in blocks, which are then stored in the Blockchain. As compared to the number of transactions in the mempool, the set of transactions which are verified but not yet confirmed, available space for inclusion in a block is typically limited. For this reason, successful miners can only process a subset of such transactions, and users compete with each other to enter the next block by offering confirmation fees. Assuming that successful miners pursue revenue maximization, they will include in the block those mempool transactions that maximize earnings from related fees. In the paper we model transaction fees as a Nash Equilibrium outcome of an auction game with complete information. In the game the successful miner acts as an auctioneer selling block space, and users bid for shares of such space to confirm their transactions. Moreover, based on expected fees we also discuss what the optimal, revenue maximizing, block size limit should be for the successful miner. Consistently with the intuition, the optimal block size limit resolves the trade-off between including additional transactions (which possibly lower the unit fees collected) and keeping the block capacity limited (with, however, higher unit fees).

This paper presents a simple game theoretic framework, assuming complete information, to model Bitcoin mining activity. It does so by formalizing the activity as an all-pay contest: a competition where participants contend with each other to win a prize by investing in computational power, and victory is probabilistic. With at least two active miners, the unique pure strategy Nash equilibrium of the game suggests the following interesting insights on the motivation for being a miner: while the optimal amount of energy consumption depends also on the reward for solving the puzzle, as long as the reward is positive the decision to be an active miner depends only on the mining costs. Moreover, the intrinsic structure of the mining activity seems to prevent the formation of a monopoly, because in an equilibrium with two miners, both of them will have positive expected profits for any level of the opponent's costs. A monopoly could only form if the rate of return on investment were higher outside bitcoin.

An arms race for an artificial general intelligence (AGI) would be detrimental for and even pose an existential threat to humanity if it results in an unfriendly AGI. In this paper an all-pay contest model is developed to derive implications for public policy to avoid such an outcome. It is established that in a winner-takes all race, where players must invest in R&D, only the most competitive teams will participate. Given the difficulty of AGI the number of competing teams is unlikely ever to be very large. It is also established that the intention of teams competing in an AGI race, as well as the possibility of an intermediate prize is important in determining the quality of the eventual AGI. The possibility of an intermediate prize will raise quality of research but also the probability of finding the dominant AGI application and hence will make public control more urgent. It is recommended that the danger of an unfriendly AGI can be reduced by taxing AI and by using public procurement. This would reduce the pay-off of contestants, raise the amount of R&D needed to compete, and coordinate and incentivize co-operation, all outcomes that will help alleviate the control and political problems in AI. Future research is needed to elaborate the design of systems of public procurement of AI innovation and for appropriately adjusting the legal frameworks underpinning high-tech innovation, in particular dealing with patents created by AI.

In recent years the understanding of the cognitive foundations of economic behavior has become increasingly important. This volume contains contributions from such leading scholars as Adam Brandenburger, Michael Bacharach and Patrick Suppes. It will be of great interest to academics and researchers involved in the field of economics and psychology as well as those interested in political economy more generally

This White Paper provides a step-by-step approach on how to procure e-mobility solutions. Chapter 1 covers the implementation of a so-called innovation procurement. Chapter 2 covers all relevant aspects that are related to the Government Procurement Agreement (GPA) of the World Trade Organization with a link to the most relevant aspects of EU Trade Agreements that enhance the competitiveness of European companies. The chapter also presents an overview of the most recent and relevant EU initiatives to maintain a level playing field in public procurement within and across the boundaries of the EU Internal Market. Chapter 3 covers the possibilities to include social and environmental criteria within government procurements. Chapter 4 concludes on the findings of the e-Mobility paper and provides the reader with useful practices and tools to follow up on the procurement of e-mobility solutions. For the context of this White Paper, e-mobility solutions are transport solutions which are based on heavy duty vehicles with a zero-emission tailpipe pollution, which are a category under article 4 (5) of the Directive 2009/33/EC of 23 April 2009 on the promotion of clean road transport vehicles in support of low-emission mobility amended by Directive (EU) 2019/1161 of the European Parliament and of the Council of 20 June 2019