Autonomous Agents and Multi-Agent Systems最新文献_第4页

Theoretical properties of the MiCRO negotiation strategy 米克罗谈判战略的理论特性

IF 2 3区计算机科学

Autonomous Agents and Multi-Agent Systems Pub Date : 2024-09-30 DOI: 10.1007/s10458-024-09678-1

Dave de Jonge

{"title":"Theoretical properties of the MiCRO negotiation strategy","authors":"Dave de Jonge","doi":"10.1007/s10458-024-09678-1","DOIUrl":"10.1007/s10458-024-09678-1","url":null,"abstract":"<div><p>Recently, we have introduced a new algorithm for automated negotiation, called MiCRO, which, despite its simplicity, outperforms many state-of-the-art negotiation strategies (de Jonge, in: Raedt (ed) Proceedings of the thirty-first international joint conference on artificial intelligence, ijcai.org, Vienna, Austria, 2022). Furthermore, we claimed that under certain conditions which typically hold in the Automated Negotiating Agents Competition (ANAC), it is a game-theoretically optimal strategy. The goal of this paper is to formally prove those claims. Specifically, we define ‘negotiation’ as an extensive-form game and define the class of <i>consistent</i> strategies for this game, which consists of those strategies that satisfy a number of rationality criteria. We then prove that under the above mentioned conditions MiCRO is a best response against itself among all consistent negotiation strategies. Furthermore, we define the notion of a <i>balanced</i> negotiation domain, which is a domain in which two MiCRO agents would always come to an optimal agreement. Finally, we show that many of the domains used in ANAC indeed happen to be (approximately) balanced. The importance of this work is that if we know under which conditions MiCRO is theoretically optimal, then we can use this to test to what extent other negotiation algorithms are able to achieve similar results to MiCRO when applied under those same conditions. Furthermore, it would help researchers to design more challenging test cases for automated negotiation in which MiCRO is not optimal.</p></div>","PeriodicalId":55586,"journal":{"name":"Autonomous Agents and Multi-Agent Systems","volume":"38 2","pages":""},"PeriodicalIF":2.0,"publicationDate":"2024-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10458-024-09678-1.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142415178","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Personalised electric vehicle charging stop planning through online estimators 通过在线估算器进行个性化电动汽车充电桩规划

IF 2 3区计算机科学

Autonomous Agents and Multi-Agent Systems Pub Date : 2024-09-30 DOI: 10.1007/s10458-024-09671-8

Elnaz Shafipour, Sebastian Stein, Selin Ahipasaoglu

{"title":"Personalised electric vehicle charging stop planning through online estimators","authors":"Elnaz Shafipour, Sebastian Stein, Selin Ahipasaoglu","doi":"10.1007/s10458-024-09671-8","DOIUrl":"10.1007/s10458-024-09671-8","url":null,"abstract":"<div><p>In this paper, we address the problem of finding charging stops while travelling in electric vehicles (EVs) using artificial intelligence (AI). Choosing a charging station is challenging, because drivers have very heterogeneous preferences in terms of how they trade off the features of various alternatives (for example, regarding the time spent driving, charging costs, waiting times at charging stations, and the facilities provided at the charging stations). The key problem here is eliciting the diverse preferences of drivers, assuming that these preferences are typically not fully known a priori, and then planning stops based on each driver’s preferences. Our approach to solving this problem is to develop an intelligent personal agent that learns preferences gradually over multiple interactions. This study proposes a new technique that utilises a small-scale discrete choice experiment as a method of interacting with the driver in order to minimise the cognitive burden on the driver. Using this method, drivers are presented with a variety of routes with possible combinations of charging stops depending on the agent’s latest belief about their preferences. In subsequent iterations, the personal agent will continue to learn and refine its belief about the driver’s preferences, suggesting more personalised routes that are closer to the driver’s preferences. Based on real preference data from EV drivers, we evaluate our novel algorithm and show that, after only a few queries, our method quickly converges to the optimal routes for EV drivers [This paper is an extended version of an ECAI workshop short paper (Shafipour Yourdshahi et al., in: ECAI 2023 workshops, Kraków, Poland, 2023)].</p></div>","PeriodicalId":55586,"journal":{"name":"Autonomous Agents and Multi-Agent Systems","volume":"38 2","pages":""},"PeriodicalIF":2.0,"publicationDate":"2024-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10458-024-09671-8.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142415137","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Strategic manipulation of preferences in the rank minimization mechanism 在等级最小化机制中对偏好的策略性操纵

IF 2 3区计算机科学

Autonomous Agents and Multi-Agent Systems Pub Date : 2024-09-24 DOI: 10.1007/s10458-024-09676-3

Mayesha Tasnim, Youri Weesie, Sennay Ghebreab, Max Baak

{"title":"Strategic manipulation of preferences in the rank minimization mechanism","authors":"Mayesha Tasnim, Youri Weesie, Sennay Ghebreab, Max Baak","doi":"10.1007/s10458-024-09676-3","DOIUrl":"10.1007/s10458-024-09676-3","url":null,"abstract":"<div><p>We consider one-sided matching problems, where agents are allocated items based on stated preferences. Posing this as an assignment problem, the average rank of obtained matchings can be minimized using the rank minimization (RM) mechanism. RM matchings can have significantly better rank distributions than matchings obtained by mechanisms with random priority, such as Random Serial Dictatorship. However, these matchings are sensitive to preference manipulation from strategic agents. In this work we consider a scenario where agents aim to be matched to their top-<i>n</i> preferred items using the RM mechanism, and strategically manipulate their preferences to achieve this. We derive a best response strategy for an agent to be assigned to their <i>n</i> most preferred items using the Hungarian algorithm, under a simplified cost function. This strategy is then extended to a first-order heuristic strategy for being matched to the top-<i>n</i> items in a setup that minimizes the average rank. Based on this finding, an empirical study is conducted examining the impact of the first-order heuristic strategy. The study utilizes data from both simulated markets and real-world matching markets in Amsterdam, taking into account variations in item popularity, fractions of strategic agents, and the preferences for the <i>n</i> most favored items. For most scenarios, RM yields more rank efficient matches than Random Serial Dictatorship, even when agents apply the first-order heuristic strategy. However, although highly market dependent, the matching performance can become worse when 50% of agents or more want to be matched to their top-1 or top-2 preferred items and apply the first-order heuristic strategy to achieve this.</p></div>","PeriodicalId":55586,"journal":{"name":"Autonomous Agents and Multi-Agent Systems","volume":"38 2","pages":""},"PeriodicalIF":2.0,"publicationDate":"2024-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10458-024-09676-3.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142413494","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multivariate algorithmics for eliminating envy by donating goods 通过捐赠物品消除嫉妒的多元算法

IF 2 3区计算机科学

Autonomous Agents and Multi-Agent Systems Pub Date : 2024-09-09 DOI: 10.1007/s10458-024-09674-5

Niclas Boehmer, Robert Bredereck, Klaus Heeger, Dušan Knop, Junjie Luo

{"title":"Multivariate algorithmics for eliminating envy by donating goods","authors":"Niclas Boehmer, Robert Bredereck, Klaus Heeger, Dušan Knop, Junjie Luo","doi":"10.1007/s10458-024-09674-5","DOIUrl":"10.1007/s10458-024-09674-5","url":null,"abstract":"<div><p>Fairly dividing a set of indivisible resources to a set of agents is of utmost importance in some applications. However, after an allocation has been implemented the preferences of agents might change and envy might arise. We study the following problem to cope with such situations: given an allocation of indivisible resources to agents with additive utility-based preferences, is it possible to socially donate some of the resources (which means removing these resources from the allocation instance) such that the resulting modified allocation is envy-free (up to one good). We require that the number of deleted resources and/or the caused utilitarian welfare loss of the allocation are bounded. We conduct a thorough study of the (parameterized) computational complexity of this problem considering various natural and problem-specific parameters (e.g., the number of agents, the number of deleted resources, or the maximum number of resources assigned to an agent in the initial allocation) and different preference models, including unary-encoded and 0/1-valuations. In our studies, we obtain a rich set of (parameterized) tractability and intractability results and discover several surprising contrasts, for instance, between the two closely related fairness concepts envy-freeness and envy-freeness up to one good and between the influence of the parameters maximum number and welfare of the deleted resources.</p></div>","PeriodicalId":55586,"journal":{"name":"Autonomous Agents and Multi-Agent Systems","volume":"38 2","pages":""},"PeriodicalIF":2.0,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142191087","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Graphical house allocation with identical valuations 估值相同的图形化房屋分配

IF 2 3区计算机科学

Autonomous Agents and Multi-Agent Systems Pub Date : 2024-08-28 DOI: 10.1007/s10458-024-09672-7

Hadi Hosseini, Andrew McGregor, Justin Payan, Rik Sengupta, Rohit Vaish, Vignesh Viswanathan

{"title":"Graphical house allocation with identical valuations","authors":"Hadi Hosseini, Andrew McGregor, Justin Payan, Rik Sengupta, Rohit Vaish, Vignesh Viswanathan","doi":"10.1007/s10458-024-09672-7","DOIUrl":"10.1007/s10458-024-09672-7","url":null,"abstract":"<div><p>The classical house allocation problem involves assigning <i>n</i> houses (or items) to <i>n</i> agents according to their preferences. A key criterion in such problems is satisfying some fairness constraints such as envy-freeness. We consider a generalization of this problem, called <span>Graphical House Allocation</span>, wherein the agents are placed along the vertices of a graph (corresponding to a social network), and each agent can only experience envy towards its neighbors. Our goal is to minimize the <i>aggregate</i> envy among the agents as a natural fairness objective, i.e., the sum of the envy value over all edges in a social graph. We focus on graphical house allocation with identical valuations. When agents have identical and <i>evenly-spaced</i> valuations, our problem reduces to the well-studied <span>Minimum Linear Arrangement</span>. For identical valuations with possibly uneven spacing, we show a number of deep and surprising ways in which our setting is a departure from this classical problem. More broadly, we contribute several structural and computational results for various classes of graphs, including NP-hardness results for disjoint unions of paths, cycles, stars, cliques, and complete bipartite graphs; we also obtain fixed-parameter tractable (and, in some cases, polynomial-time) algorithms for paths, cycles, stars, cliques, complete bipartite graphs, and their disjoint unions. Additionally, a conceptual contribution of our work is the formulation of a structural property for disconnected graphs that we call <i>splittability</i>, which results in efficient parameterized algorithms for finding optimal allocations.</p></div>","PeriodicalId":55586,"journal":{"name":"Autonomous Agents and Multi-Agent Systems","volume":"38 2","pages":""},"PeriodicalIF":2.0,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142191089","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Truthful interval covering 真实区间覆盖

IF 2 3区计算机科学

Autonomous Agents and Multi-Agent Systems Pub Date : 2024-08-20 DOI: 10.1007/s10458-024-09673-6

Argyrios Deligkas, Aris Filos-Ratsikas, Alexandros A. Voudouris

{"title":"Truthful interval covering","authors":"Argyrios Deligkas, Aris Filos-Ratsikas, Alexandros A. Voudouris","doi":"10.1007/s10458-024-09673-6","DOIUrl":"10.1007/s10458-024-09673-6","url":null,"abstract":"<div><p>We initiate the study of a novel problem in mechanism design without money, which we term <i>Truthful Interval Covering</i> (TIC). An instance of TIC consists of a set of agents each associated with an individual interval on a line, and the objective is to decide where to place a <i>covering interval</i> to minimize the total social or egalitarian cost of the agents, which is determined by the intersection of this interval with their individual ones. This fundamental problem can model situations of provisioning a public good, such as the use of power generators to prevent or mitigate load shedding in developing countries. In the strategic version of the problem, the agents wish to minimize their individual costs, and might misreport the position and/or length of their intervals to achieve that. Our goal is to design <i>truthful</i> mechanisms to prevent such strategic misreports and achieve good approximations to the best possible social or egalitarian cost. We consider the fundamental setting of known intervals with equal lengths and provide tight bounds on the approximation ratios achieved by truthful deterministic mechanisms. For the social cost, we also design a randomized truthful mechanism that outperforms all possible deterministic ones. Finally, we highlight a plethora of natural extensions of our model for future work, as well as some natural limitations of those settings.</p></div>","PeriodicalId":55586,"journal":{"name":"Autonomous Agents and Multi-Agent Systems","volume":"38 2","pages":""},"PeriodicalIF":2.0,"publicationDate":"2024-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10458-024-09673-6.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142191088","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

One-sided matching markets with endowments: equilibria and algorithms 有禀赋的单边匹配市场：均衡与算法

IF 2 3区计算机科学

Autonomous Agents and Multi-Agent Systems Pub Date : 2024-08-12 DOI: 10.1007/s10458-024-09670-9

Jugal Garg, Thorben Tröbst, Vijay Vazirani

{"title":"One-sided matching markets with endowments: equilibria and algorithms","authors":"Jugal Garg, Thorben Tröbst, Vijay Vazirani","doi":"10.1007/s10458-024-09670-9","DOIUrl":"10.1007/s10458-024-09670-9","url":null,"abstract":"<div><p>The Arrow–Debreu extension of the classic Hylland–Zeckhauser scheme (Hylland and Zeckhauser in J Polit Econ 87(2):293–314, 1979) for a one-sided matching market—called ADHZ in this paper—has natural applications but has instances which do not admit equilibria. By introducing approximation, we define the <span>(epsilon)</span><i>-approximate ADHZ model</i> and give the following results. 1. Existence of equilibrium under linear utility functions. We prove that the equilibrium allocation satisfies Pareto optimality, approximate envy-freeness, and approximate weak core stability. 2. A combinatorial polynomial time algorithm for an <span>(epsilon)</span>-approximate ADHZ equilibrium for the case of dichotomous, and more generally bi-valued, utilities. 3. An instance of ADHZ, with dichotomous utilities and a strongly connected demand graph, which does not admit an equilibrium. 4. A rational convex program for HZ under dichotomous utilities; a combinatorial polynomial time algorithm for this case was given in Vazirani and Yannakakis (in: Innovations in theoretical computer science, pp 59–15919, 2021). The <span>(epsilon)</span>-approximate ADHZ model fills a void in the space of general mechanisms for one-sided matching markets; see details in the paper.</p></div>","PeriodicalId":55586,"journal":{"name":"Autonomous Agents and Multi-Agent Systems","volume":"38 2","pages":""},"PeriodicalIF":2.0,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141948434","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Efficiently reconfiguring a connected swarm of labeled robots 高效重新配置连接的贴标机器人群

IF 2 3区计算机科学

Autonomous Agents and Multi-Agent Systems Pub Date : 2024-08-07 DOI: 10.1007/s10458-024-09668-3

Sándor P. Fekete, Peter Kramer, Christian Rieck, Christian Scheffer, Arne Schmidt

{"title":"Efficiently reconfiguring a connected swarm of labeled robots","authors":"Sándor P. Fekete, Peter Kramer, Christian Rieck, Christian Scheffer, Arne Schmidt","doi":"10.1007/s10458-024-09668-3","DOIUrl":"10.1007/s10458-024-09668-3","url":null,"abstract":"<div><p>When considering motion planning for a swarm of <i>n</i> labeled robots, we need to rearrange a given start configuration into a desired target configuration via a sequence of parallel, collision-free moves. The objective is to reach the new configuration in a minimum amount of time. Problems of this type have been considered before, with recent notable results achieving <i>constant stretch</i> for parallel reconfiguration: If mapping the start configuration to the target configuration requires a maximum Manhattan distance of <i>d</i>, the total duration of an overall schedule can be bounded to <span>(mathcal {O}(d))</span>, which is optimal up to constant factors. An important constraint for coordinated reconfiguration is to keep the swarm connected after each time step. In previous work, constant stretch could only be achieved if <i>disconnected</i> reconfiguration is allowed, or for scaled configurations of <i>unlabeled</i> robots; on the other hand, the existence of non-constant lower bounds on the stretch factor was unknown. We resolve these major open problems by (1) establishing a lower bound of <span>(Omega (sqrt{n}))</span> for connected, labeled reconfiguration and, most importantly, by (2) proving that for scaled arrangements, constant stretch for connected, labeled reconfiguration can be achieved. In addition, we show that (3) it is <span>NP</span>-complete to decide whether a makespan of 2 can be achieved, while it is possible to check in polynomial time whether a schedule of makespan 1 exists.</p></div>","PeriodicalId":55586,"journal":{"name":"Autonomous Agents and Multi-Agent Systems","volume":"38 2","pages":""},"PeriodicalIF":2.0,"publicationDate":"2024-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10458-024-09668-3.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141948435","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Carbon trading supply chain management based on constrained deep reinforcement learning 基于约束深度强化学习的碳交易供应链管理

IF 2 3区计算机科学

Autonomous Agents and Multi-Agent Systems Pub Date : 2024-08-06 DOI: 10.1007/s10458-024-09669-2

Qinghao Wang, Yaodong Yang

{"title":"Carbon trading supply chain management based on constrained deep reinforcement learning","authors":"Qinghao Wang, Yaodong Yang","doi":"10.1007/s10458-024-09669-2","DOIUrl":"10.1007/s10458-024-09669-2","url":null,"abstract":"<div><p>The issue of carbon emissions is a critical global concern, and how to effectively reduce energy consumption and emissions is a challenge faced by the industrial sector, which is highly emphasized in supply chain management. The complexity arises from the intricate coupling mechanism between carbon trading and ordering. T he large-scale state space involved and various constraints make cost optimization difficult. Carbon quota constraints and sequential decision-making exacerbate the challenges for businesses. Existing research implements rule-based and heuristic numerical simulation, which struggles to adapt to time-varying environments. We develop a unified framework from the perspective of Constrained Markov Decision Processes (CMDP). Constrained Deep Reinforcement Learning (DRL) with its powerful high-dimensional representations of neural networks and effective decision-making capabilities under constraints, provides a potential solution for supply chain management that includes carbon trading. DRL with constraints is a crucial tool to study cost optimization for enterprises. This paper constructs a DRL algorithm for Double Order based on PPO-Lagrangian (DOPPOL), aimed at addressing a supply chain management model that integrates carbon trading decisions and ordering decisions. The results indicate that businesses can optimize both business and carbon costs, thereby increasing overall profits, as well as adapt to various demand uncertainties. DOPPOL outperforms the traditional method (<i>s</i>, <i>S</i>) in fluctuating demand scenarios. By introducing carbon trading, enterprises are able to adjust supply chain orders and carbon emissions through interaction, and improve operational efficiency. Finally, we emphasize the significant role of carbon pricing in enterprise contracts in terms of profitability, as reasonable prices can help control carbon emissions and reduce costs. Our research is of great importance in achieving climate change control, as well as promoting sustainability.</p></div>","PeriodicalId":55586,"journal":{"name":"Autonomous Agents and Multi-Agent Systems","volume":"38 2","pages":""},"PeriodicalIF":2.0,"publicationDate":"2024-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141948436","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Envy-freeness in 3D hedonic games 三维享乐游戏中的羡慕嫉妒恨

IF 2 3区计算机科学

Autonomous Agents and Multi-Agent Systems Pub Date : 2024-07-30 DOI: 10.1007/s10458-024-09657-6

Michael McKay, Ágnes Cseh, David Manlove

引用次数: 0