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Transactive Energy for Flexible Prosumers Using algorithmic game theory

IEEE TRANSACTIONS ON SUSTAINABLE ENERGY 2021年第3期12卷 1571-1581页

作者： Tsaousoglou, Georgios Pinson, Pierre Paterakis, Nikolaos G. Eindhoven Univ Technol NL-5612 AZ Eindhoven Netherlands Tech Univ Denmark DK-2800 Lyngby Denmark

In modern smart grids, the focus is increasingly shifted towards distributed energy resources and flexible electricity assets owned by prosumers. A system with high penetration of flexible prosumers, has a very large number of variables and constraints, while a lot of the information is local and non-observable. Decomposition methods and local problem solving is considered a promising approach for such settings, particularly when the implementation of a decomposition method features a market-based analogy, i.e. it can be implemented in a Transactive Energy fashion. In this paper we present an auction-theoretic scheme for a setting with non-convex prosumer models and resource constraints. The scheme is evaluated on a particular case study and its scalability and efficiency properties are tested and compared to an optimal benchmark solution. A game-theoretic analysis is made with respect to how an intelligent agent, that bids on behalf of a prosumer can try to strategize within the auction, in order to make itself better-off. Our simulations show that there is an alignment of incentives, i.e., when the prosumers try to strategize, they actually improve the auction's efficiency.

关键词： Energy management Scalability Intelligent agents Transactive energy Tools Smart grids Resource management Flexibility transactive energy algorithmic game theory auction

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Simple reinforcement learning agents: Pareto beats Nash in an algorithmic game theory study

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Information Systems and e-Business Management 2005年第1期3卷 1-19页

作者： Kimbrough, Steven O. Lu, Ming Operation/Info. Mgmt. Department The Wharton School University of Pennsylvania Philadelphia PA 19104-6340 500 Jon M. Huntsman Hall United States

Repeated play in games by simple adaptive agents is investigated. The agents use Q-learning, a special form of reinforcement learning, to direct learning of behavioral strategies in a number of 2 × 2 games. The agents are able effectively to maximize the total wealth extracted. This often leads to Pareto optimal outcomes. When the rewards signals are sufficiently clear, Pareto optimal outcomes will largely be achieved. The effect can select Pareto outcomes that are not Nash equilibria and it can select Pareto optimal outcomes among Nash equilibria. © Springer-Verlag 2005.

关键词： algorithmic game theory games Learning and games Q-learning

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Securing Majority-Attack in Blockchain Using Machine Learning and algorithmic game theory: A Proof of Work 10

Securing Majority-Attack in Blockchain Using Machine Learnin...

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10th Computer Science and Electronic Engineering Conference (CEEC)

作者： Dey, Somdip Univ Essex Sch Comp Sci & Elect Engn Colchester Essex England

ISBN: (纸本)9781538672754

Recently we could see several institutions coming together to create consortium based blockchain networks such as Hyperledger. Although for applications of blockchain such as Bitcoin, Litcoin, etc. the majority-attack might not be a great threat but for consortium based blockchain networks where we could see several institutions such as public, private, government, etc. are collaborating, the majority-attack might just prove to be a prevalent threat if collusion among these institutions takes place. This paper proposes a methodology where we can use intelligent software agents to monitor the activity of stakeholders in the blockchain networks to detect anomaly such as collusion, using supervised machine learning algorithm and algorithmic game theory and stop the majority-attack from taking place.

关键词： Computer Security network blockchain machine learning algorithmic game theory majority attack anomaly detection

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Modeling Human Interactions: Facets of algorithmic game theory and Computational Social Choice 14

Modeling Human Interactions: Facets of Algorithmic Game Theo...

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International Conference on Autonomous Agents and Multiagent Systems

作者： Omer Lev School of Computer Science and Engineering Hebrew University

ISBN: (纸本)9781634391313

Modeling human activities and interactions - especially when participants exhibit rational behavior - has long been a research goal in economics, mathematics (specifically, game theory), and computer science. In computer science, this was initially framed in the classical sense of artificial intelligence (AI), in which attempts were made to mimic human behavior. However, in the past 20 years, especially since the advent of the World Wide Web and the explosion in the number of people interacting using various computing systems, research in the field has expanded dramatically. In particular, there is a significant and growing interest in the types of interactions commonly seen on the web: (1) Auctions: Auction-like mechanisms are at the heart of the ad-generated profit model powering most websites, as the major ad-selling networks perform virtual auctions to sell ad space. Furthermore, auctions model many human interactions that are non-commercial: for example, all-pay auctions, in which all participants pay their bid, regardless of who wins, can be used to model a job market, in which all job-seekers are, in effect, bidding for a job, and putting in effort to get it, regardless of whether or not they eventually succeed. (2) Voting: When several people, or agents, need to decide on what option to pursue, some mechanism is needed to decide among their respective preferences. Such elections, whether they involve a large or small number of participants, occur all around us, outside political contexts, like when choosing a restaurant for dinner. While it may seem straightforward to simply choose an election method, different voting rules have different properties and potentially different outcomes; in addition, the choice is complicated by the proven lack of a strategy-proof voting mechanism. (3) Crowdsourcing: When multiple people are working together towards a shared goal, various problems arise: how to incentivize massive participation, how to decide among differing op

关键词： algorithmic game theory auction theory computational social choice

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New bounds on the price of anarchy of selfish bin packing with partial punishment

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JOURNAL OF COMBINATORIAL OPTIMIZATION 2025年第1期49卷 1-17页

作者： Li, Xiaowei Liu, Peihai Lu, Xiwen East China Univ Sci & Technol Coll Math Shanghai 200237 Peoples R China

The selfish bin packing with partial punishment is studied in this paper. In this problem, the utility of an item is defined as the load of the bin it is in. Each item plays the role of a selfish agent and wants to maximize its own utility. If an item with size si moves to another bin, it has to pay the partial punishment of alpha s i , where 0 < alpha < 1. We prove that the price of anarchy (PoA) of this game is at least 1.6424 for any alpha is an element of (0 , 1). In particular, the PoA of this game is at least 5/3 approximate to 1.6667 for any alpha is an element of (2/5, 1). Furthermore, we obtain a new upper bound of h (alpha) <= 31/18 approximate to 1.7222 on the PoA.

关键词： algorithmic game theory Selfish bin packing Price of anarchy Nash equilibrium

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PLAYING STOCHASTICALLY IN WEIGHTED TIMED gameS TO EMULATE MEMORY

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LOGICAL METHODS IN COMPUTER SCIENCE 2025年第1期21卷 19:1-19:61页

作者： Monmege, Benjamin Parreaux, Julie Reynier, Pierre-alain Aix Marseille Univ CNRS LIS Marseille France Univ Warsaw Warsaw Poland

Weighted timed games are two-player zero-sum games played in a timed automaton equipped with integer weights. We consider optimal reachability objectives, in which one of the players, that we call Min, wants to reach a target location while minimising the cumulated weight. While knowing if Min has a strategy to guarantee a value lower than a given threshold is known to be undecidable (with two or more clocks), several conditions, one of them being divergence, have been given to recover decidability. In such weighted timed games (like in untimed weighted games in the presence of negative weights), Min may need finite memory to play (close to) optimally. This is thus tempting to try to emulate this finite memory with other strategic capabilities. In this work, we allow the players to use stochastic decisions, both in the choice of transitions and of timing delays. We give a definition of the expected value in weighted timed games. We then show that, in divergent weighted timed games as well as in (untimed) weighted games (that we call shortest-path games in the following), the stochastic value is indeed equal to the classical (deterministic) value, thus proving that Min can guarantee the same value while only using stochastic choices, and no memory.

关键词： weighted timed games algorithmic game theory timed automata stochastic strategies

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The Last Survivor of PoS Pools: Staker's Dilemma

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PROCEEDINGS OF THE ACM ON MEASUREMENT AND ANALYSIS OF COMPUTING SYSTEMS 2025年第1期9卷 1-29页

作者： Huang, Yuming Tang, Jing Cong, Qianhao Ma, Richard T. B. Chen, Lei Chee, Yeow Meng Natl Univ Singapore Singapore Singapore Hong Kong Univ Sci & Technol Guangzhou Peoples R China

In blockchains using the Proof-of-Work (PoW) consensus mechanism, a mining pool is a joint group of miners who combine their computational resources and share the generated revenue. Similarly, when the Proof-of-Stake (PoS) consensus mechanism is adopted, the staking pool imitates the design of the mining pool by aggregating the stakes. However, in PoW blockchains, the pooling approach has been criticized to be vulnerable to the block withholding (BWH) attack. BWH attackers may steal the dividends from victims by pretending to work but making invalid contributions to the victim pools. It is well known that BWH attackers against PoW face the miner's dilemma. To our knowledge, despite the popularity of PoS, we are the first to study the pool BWH attack against PoS. Interestingly, we find that, for a network only consisting of one attacker pool and one victim pool, the attacker will eventually manipulate the network while the victim will vanish by losing the stake ratio gradually. Moreover, in a more realistic scenario with multiple BWH attacker pools and one solo staker who does not join any pools, we show that only one lucky attacker and the solo staker will survive, whereas all the other pools will vanish gradually, revealing the staker's dilemma. These findings indicate that, compared to PoW, the BWH attack on PoS has a much more severe impact due to the attacker's resource aggregation advantage. Our analysis is supported by experiments on massive real blockchain systems and numerical simulations.

关键词： theory of computation algorithmic game theory Security and privacy Distributed systems security Mathematics of computing Stochastic processes

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Simple Stochastic Stopping games: A Generator and Benchmark Library 8th

Simple Stochastic Stopping Games: A Generator and Benchmark ...

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8th International Conference on algorithmic Decision theory

作者： Rudich, Avi Rudich, Isaac Rue, Rachel Polytech Montreal Montreal PQ Canada

ISBN: (纸本)9783031739026;9783031739033

Stochastic games are used for modeling decision-making processes in environments characterized by uncertainty and adversarial interactions. They are particularly relevant for multi-agent systems, where understanding the equilibrium of multiple decision-makers is essential. Simple Stochastic games (SSGs) were introduced by Anne Condon in 1990, as the simplest version of Stochastic games for which there is no known polynomial-time algorithm [5]. Condon showed that Stochastic games are polynomial-time reducible to SSGs, which in turn are polynomial-time reducible to Stopping games. SSGs are games where all decisions are binary and every move has a random outcome with a known probability distribution. Stopping games are SSGs that are guaranteed to terminate. There are many algorithms for SSGs, most of which are fast in practice, but they all lack theoretical guarantees for polynomial-time convergence. The pursuit of a polynomial-time algorithm for SSGs is an active area of research. This paper is intended to support such research by making it easier to study the graphical structure of SSGs. Our contributions are: (1) a generating algorithm for Stopping games, (2) a proof that the algorithm can generate any game, (3) a list of additional polynomial-time reductions that can be made to Stopping games, (4) an open source generator for generating fully reduced instances of Stopping games that comes with instructions and is fully documented, (5) a benchmark set of such instances, (6) and an analysis of how two main algorithm types perform on our benchmark set.

关键词： Stochastic games Decision theory algorithmic game theory

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Stable Matching with Interviews 16

Stable Matching with Interviews

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16th Innovations in Theoretical Computer Science Conference, ITCS 2025

作者： Ashlagi, Itai Chen, Jiale Roghani, Mohammad Saberi, Amin Stanford University CA United States

ISBN: (纸本)9783959773614

In several two-sided markets, including labor and dating, agents typically have limited information about their preferences prior to mutual interactions. This issue can result in matching frictions, as arising in the labor market for medical residencies, where high application rates are followed by a large number of interviews. Yet, the extensive literature on two-sided matching primarily focuses on models where agents know their preferences, leaving the interactions necessary for preference discovery largely overlooked. This paper studies this problem using an algorithmic approach, extending Gale-Shapley’s deferred acceptance to this context. Two algorithms are proposed. The first is an adaptive algorithm that expands upon Gale-Shapley’s deferred acceptance by incorporating interviews between applicants and positions. Similar to deferred acceptance, one side sequentially proposes to the other. However, the order of proposals is carefully chosen to ensure an interim stable matching is found. Furthermore, with high probability, the number of interviews conducted by each applicant or position is limited to O(log2 n). In many seasonal markets, interactions occur more simultaneously, consisting of an initial interview phase followed by a clearing stage. We present a non-adaptive algorithm for generating a single stage set of in tiered random markets. The algorithm finds an interim stable matching in such markets while assigning no more than O(log3 n) interviews to each applicant or position. © Itai Ashlagi, Jiale Chen, Mohammad Roghani, and Amin Saberi.

关键词： algorithmic game theory Gale–Shapley Algorithm Stable Matching

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DECIDABILITY OF ONE-CLOCK WEIGHTED TIMED gameS WITH ARBITRARY WEIGHTS

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LOGICAL METHODS IN COMPUTER SCIENCE 2025年第1期21卷

作者： Monmege, Benjamin Parreaux, Julie Reynier, Pierre-alain Aix Marseille Univ CNRS LIS Marseille France Univ Warsaw Warsaw Poland

. Weighted Timed games (WTG for short) are the most widely used model to describe controller synthesis problems involving real-time issues. Unfortunately, they are notoriously difficult, and undecidable in general. As a consequence, one-clock WTGs have attracted a lot of attention, especially because they are known to be decidable when only non-negative weights are allowed. However, when arbitrary weights are considered, despite several recent works, their decidability status was still unknown. In this paper, we solve this problem positively and show that the value function can be computed in exponential time (if weights are encoded in unary).

关键词： Key words and phrases weighted timed games algorithmic game theory timed automata value computation

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