Autonomous Agents and Multi-Agent Systems最新文献

{"title":"Enhancing sentiment analysis accuracy: strategic pre-calibration to mitigate anchoring bias","authors":"Jonathan Schler,&nbsp;Idan Toker,&nbsp;David Sarne","doi":"10.1007/s10458-026-09763-7","DOIUrl":"10.1007/s10458-026-09763-7","url":null,"abstract":"<div><p>In this study, we explore the concept of anchoring bias in the context of sequential sentiment analysis of review corpora. We introduce a novel approach that involves using a carefully selected, limited group of reviews at the beginning of the annotation process for calibration, aiming to reduce this bias. Through an extensive set of experiments we confirm the existence of sentiment bias and demonstrate that indeed its impact can be moderated through initial calibration. We also demonstrate that the composition of the calibration set is critical, underscoring the importance of establishing sound criteria for selecting these initial reviews. By comparing the accuracy of annotators who utilized our calibration method against those who did not calibrate or used a randomly chosen set for calibration, we found that our method significantly decreases the overall annotation error. Moreover, the guidelines we develop for selecting the calibration set prove to be highly effective and adaptable, even when applied to a domain other than the one they were originally developed for. Acknowledging the overhead of labeling calibration reviews, we demonstrate that this approach is more efficient compared to eliciting multiple sentiment scores per review, a common strategy to reduce Mean Absolute Error (MAE). Our findings reveal that the proposed calibration method significantly reduces resource expenditure, compared to relying on parallel labeling, while maintaining accuracy.</p></div>","PeriodicalId":55586,"journal":{"name":"Autonomous Agents and Multi-Agent Systems","volume":"40 2","pages":""},"PeriodicalIF":2.4,"publicationDate":"2026-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10458-026-09763-7.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148614112","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}

{"title":"Computing exact optimal covers for cover function games with approximate ordinal input","authors":"Syeda Shaheen Fatima","doi":"10.1007/s10458-026-09756-6","DOIUrl":"10.1007/s10458-026-09756-6","url":null,"abstract":"<div><p>For <i>cover function games</i> (CoFGs), we address the problem of organising agents into possibly overlapping coalitions so as to maximise social welfare. We introduce a subclass of CoFGs called <i>probabilistically monotone</i> CoFGs. <i>Monotonicity</i> means that the closer a cover is to an optimum, the higher its welfare. Probabilistic monotonicity means that monotonicity is satisfied with some probability, i.e., some violations of monotonicity are permitted as long as the number of violations is bounded. In addition, <i>externalities</i> are permitted and social welfare is not restricted to the sum function. For such games, we obtain a bound on the number of monotonicity violations that can be permitted for computing an exact optimum. For probabilistically monotone CoFGs with a bound on the number of monotonicity violations, we devise algorithms for computing an exact optimum and analyze their time complexities. We also provide constructive proofs which form the basis for our algorithms. Placing our algorithms in the context of the existing literature, we note that a key unique feature of our algorithms is that they do not require the numeric welfare values of covers as input, rather, only an ordering over these values is required. Moreover, the ordering that is required as input does not have to be the actual ordering over the welfare values, it can be an approximate anticipated version of the actual ordering. The anticipated ordering is allowed to differ from the actual ordering in that anticipation errors, captured by monotonicity violations, are permitted in the anticipated ordering as long as the number of errors is bounded. Our algorithms are therefore highly relevant for practical applications like multi-agent task allocation where welfare values are only revealed after coalition formation although an ordering over the values can be approximately anticipated in advance of coalition formation.</p></div>","PeriodicalId":55586,"journal":{"name":"Autonomous Agents and Multi-Agent Systems","volume":"40 2","pages":""},"PeriodicalIF":2.4,"publicationDate":"2026-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10458-026-09756-6.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148613604","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}

{"title":"Generosity and forgiveness: The importance of nuanced reputation","authors":"Nathan Griffiths,&nbsp;Nir Oren","doi":"10.1007/s10458-026-09761-9","DOIUrl":"10.1007/s10458-026-09761-9","url":null,"abstract":"<div><p>Indirect reciprocity, supported by simple reputation assessment and social norms, has been demonstrated as an effective mechanism for enabling cooperation in populations of self-interested individuals. However, it has been shown that where there is noise in the performance of actions, or in observers’ perceptions, cooperation may not emerge. Higher-order social norms and generosity have been investigated as potential mechanisms to support cooperation in such environments, but are ineffective without additional, limiting, assumptions. In particular, higher-order norms have typically been investigated in cases where reputation is binary (‘good’ or ‘bad’) and where all agents ascribe the same reputation to an individual, implying full and perfect observation of actions. Generosity with an ‘aligned’ strategy, where all agents have the same likelihood of being generous, has been shown to be ineffective where reputation is binary. In this work we consider reciprocity emergence mechanisms in noisy domains and where agent observations may be incomplete or inaccurate. Our hypothesis is that nuanced reputation scores will enable generosity to be more effective, since an individual act of generosity will have a less extreme impact on reputation. We also investigate whether replacing the ‘aligned’ setting for generosity with a ‘non-aligned’ alternative, which we refer to as forgiveness, will support cooperation in noisy partially observable environments, without the level of ‘unjustified benevolence’ exhibited by generosity. We show both analytically and empirically that generosity when combined with fine grained reputation can help cooperation emerge, and that forgiveness can support cooperation in certain settings.</p></div>","PeriodicalId":55586,"journal":{"name":"Autonomous Agents and Multi-Agent Systems","volume":"40 2","pages":""},"PeriodicalIF":2.4,"publicationDate":"2026-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10458-026-09761-9.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148323223","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}

{"title":"Parameterized complexity of incomplete connected fair division","authors":"Harmender Gahlawat,&nbsp;Meirav Zehavi","doi":"10.1007/s10458-026-09760-w","DOIUrl":"10.1007/s10458-026-09760-w","url":null,"abstract":"<div><p><i>Fair division</i> of resources among competing agents is a fundamental problem in computational social choice and game theory. It has been intensively studied for various types of items (<i>divisible</i> and <i>indivisible</i>) and under various notions of <i>fairness</i>. We focus on <span>Connected Fair Division</span> (<span>(textsf{CFD})</span>), the variant of fair division on graphs, where the <i>resources</i> are modeled as an <i>item graph</i>. Here, each agent has to be assigned a connected subgraph of the item graph, and each item has to be assigned to some agent. We introduce a generalization of <span>(textsf{CFD})</span>, termed <span>Incomplete</span> <span>(textsf{CFD})</span> (<span>(textsf{ICFD})</span>), where exactly <i>p</i> vertices of the item graph should be assigned to the agents. This might be useful, in particular when the allocations are intended to be “economical” as well as fair. We consider four well-known notions of fairness: <span>(textsf{PROP})</span>, <span>(textsf{EF})</span>, <span>(textsf{EF1})</span>, <span>(textsf{EFX})</span>. First, we prove that <span>(textsf{EF})</span>-<span>(textsf{ICFD})</span>, <span>(textsf{EF1})</span>-<span>(textsf{ICFD})</span>, and <span>(textsf{EFX})</span>-<span>(textsf{ICFD})</span> are W[1]-hard parameterized by <i>p</i> plus the number of agents, even for graphs having constant <i>vertex cover number</i> (<span>(textsf{vcn})</span>). In contrast, we present a randomized <span>(textsf{FPT})</span> algorithm for <span>(textsf{PROP})</span>-<span>(textsf{ICFD})</span> parameterized only by <i>p</i>. Additionally, we prove both positive and negative results concerning the kernelization complexity of <span>(textsf{ICFD})</span> under all four fairness notions, parameterized by <i>p</i>, <span>(textsf{vcn})</span>, and the total number of different valuations in the item graph (<span>(textsf{val})</span>).</p></div>","PeriodicalId":55586,"journal":{"name":"Autonomous Agents and Multi-Agent Systems","volume":"40 2","pages":""},"PeriodicalIF":2.4,"publicationDate":"2026-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10458-026-09760-w.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148323387","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}

{"title":"AEGIS-RL: Abstract, Explainable Graphs for Integrated Safety in RL","authors":"Tuan Le,&nbsp;Risal Shefin,&nbsp;Debashis Gupta,&nbsp;Thai Le,&nbsp;Sarra Alqahtani","doi":"10.1007/s10458-026-09749-5","DOIUrl":"10.1007/s10458-026-09749-5","url":null,"abstract":"<div><p>Ensuring the safety of reinforcement learning (RL) policies in high-stakes environments requires more than formal verification: it needs interpretability and targeted falsification—the deliberate search for counter-examples that expose potential failures before deployment. We present AEGIS-RL (Abstract, Explainable Graphs for Integrated Safety in RL), a hybrid framework that unifies (1) explainable RL, (2) probabilistic model checking, and (3) risk-guided falsification, and augments them with (4) a lightweight runtime safety shield that switches to a fallback policy when estimated risk exceeds a threshold. AEGIS-RL first builds a directed, semantically meaningful graph from offline trajectories that blends local and global explanations to make policy behavior transparent and verifier-friendly. This abstract graph is fed to a probabilistic model checker (e.g., Storm) to verify temporal safety specifications; when violations exist, the checker returns interpretable counterexample traces that pinpoint how the policy fails. When specifications appear satisfied, AEGIS-RL estimates residual risk during checking to steer falsification toward high-risk, under-explored states, broadening coverage beyond the offline data. Across safety-critical benchmarks including two MuJoCo tasks and a medical insulin-dosing scenario; AEGIS-RL uncovers significantly more violations than uncertainty- and fuzzing-based baselines and yields a broader, more novel set of failure trajectories. The resulting explanations and counterexamples provide actionable guidance to understand, debug, and repair unsafe policies while enabling runtime mitigation without retraining.</p></div>","PeriodicalId":55586,"journal":{"name":"Autonomous Agents and Multi-Agent Systems","volume":"40 2","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10458-026-09749-5.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148236919","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}

{"title":"(textsf {EFX}) allocations and orientations on bipartite multi-graphs: a complete picture","authors":"Mahyar Afshinmehr,&nbsp;Alireza Danaei,&nbsp;Mehrafarin Kazemi,&nbsp;Kurt Mehlhorn,&nbsp;Nidhi Rathi","doi":"10.1007/s10458-026-09754-8","DOIUrl":"10.1007/s10458-026-09754-8","url":null,"abstract":"<div><p>We consider the fundamental problem of <i>fairly</i> allocating a set of indivisible items among agents having valuations that are represented by a <i>multi-graph</i> – here, agents appear as vertices and items as edges between them and each vertex (agent) only values the set of its incident edges (items). The goal is to find a fair, i.e., <i>envy-free up to any item</i> (<span>(textsf {EFX})</span>) allocation. This model has recently been introduced by [22] where they show that <span>(textsf {EFX})</span> allocations always exist on simple graphs for <i>monotone</i> valuations, i.e., where any two agents can share at most one edge (item). A natural question arises as to what happens when we go beyond simple graphs and study various classes of multi-graphs? We answer the above question affirmatively for the valuation class of <i>bipartite multi-graphs</i> and <i>multi-cycles</i>. The main contribution of this work is to establish the existence of <span>(textsf {EFX})</span> allocations on bipartite multi-graphs for <i>monotone</i> valuations and on multi-cycles for <span>(textsf {MMS})</span><i>-feasible</i> valuations. We also present pseudo-polynomial time algorithms to compute <span>(textsf {EFX})</span> allocations for the above settings. Furthermore, we show that for bipartite multi-graphs with <i>cancelable</i> valuations, <span>(textsf {EFX})</span> allocations can be computed in polynomial time. We thus deepen the understanding of <span>(textsf {EFX})</span> allocations by expanding the spectrum of settings in which they are guaranteed to exist for an arbitrary number of agents. Next, we study <span>(textsf {EFX})</span> <i>orientations</i> (allocations where every item is assigned to one of its two endpoint agents) and provide a complete characterization of their existence on bipartite multi-graphs in terms of two key parameters—the number of edges shared between any two agents and the diameter of the graph. Finally, we prove that it is <span>(textsf {NP})</span>-complete to determine whether a given fair division instance on a bipartite multi-graph admits an <span>(textsf {EFX})</span> orientation, even with a constant number of agents.</p></div>","PeriodicalId":55586,"journal":{"name":"Autonomous Agents and Multi-Agent Systems","volume":"40 2","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10458-026-09754-8.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148104244","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}

{"title":"Traveling salesman games: semicore allocations for collaborative transportation in short food supply chains","authors":"Nicolas Besson,&nbsp;Sylvain Bouveret,&nbsp;Nadia Brauner,&nbsp;Nicolas Brulard","doi":"10.1007/s10458-026-09757-5","DOIUrl":"10.1007/s10458-026-09757-5","url":null,"abstract":"<div><p>In the context of collaborative transportation in short food supply chains, we aim to theoretically characterize semicore allocations and Traveling Salesman Games (TSG). The objective is to help a group of agents (in our case, farmers) to pool the pickup and delivery facilities by proposing (i) an optimal solution for the transportation problem and (ii) a practical method to allocate induced costs among the agents in an explainable and fair way. Based on discussions with the logistics manager of an association of farmers, we argue that the semicore is a seemingly reasonable solution concept. Finding allocations in the semicore is less computationally demanding than in other solution concepts such as the core while conveying fairness concepts that can be arguably easily understood without a deep understanding of mathematical language, as opposed to other methods from cooperative game theory (such as the Shapley value or the nucleolus). Applying this concept to the development of a Decision Support System (DSS) naturally raises the question of whether there could be instances of the TSG that can have an empty semicore (like it can be the case for the core). In this paper we first provide a necessary and sufficient condition for the semicore of an instance of the TSG to be empty. Then, we prove that the set of cost functions that characterize Symmetric TSGs is a union of polyhedra. Implementing this characterization as a Satisfiability Modulo Theories (SMT) program, we are able to exhibit instances of the symmetric TSG with 6 or more players where the semicore is indeed empty. To further complete the characterization of the semicore of TSGs, we provide a proof of the NP-hardness of deciding semicore non-emptiness, which implies that it remains computationally hard to compute semicore allocations. We advocate that precisely knowing when the semicore can be empty is crucial for the DSS we aim to develop, to warn the stakeholders in some situations that a fair allocation might not exist. Finally, we conclude by giving a short description of the proof of concept of a first version of our DSS.</p></div>","PeriodicalId":55586,"journal":{"name":"Autonomous Agents and Multi-Agent Systems","volume":"40 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148172665","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}

{"title":"Concise representations and complexity results for welfare-maximizing combinatorial assignment","authors":"Fredrik Präntare,&nbsp;Leif Eriksson,&nbsp;George Osipov,&nbsp;Fredrik Heintz,&nbsp;Peter Jonsson","doi":"10.1007/s10458-026-09753-9","DOIUrl":"10.1007/s10458-026-09753-9","url":null,"abstract":"<div><p>We revisit the computational problem of partitioning indivisibles into bundles among alternatives to maximize value (e.g., welfare). These problems have broad applications, yet many important variants are computationally hard, including well-known instances in operations research, computational economics, and artificial intelligence. To address this complexity, we analyze novel restrictions and concise representations for this problem class and establish new complexity results. Building on these findings, we present improved complexity bounds using a hypergraph-based characterization and introduce a novel “bootstrapped” dynamic programming method that significantly outperforms existing algorithms for a broad class of problems. Other findings include: polynomial-time solvability for problems with non-negative synergies and two alternatives; the problem remaining <span>NP</span>-hard even when bounding bundle sizes to two, with other instances being polynomial-time solvable; and exploration of bounds for more general cases allowing externalities and balanced (mixed) welfare, offering efficient approximation and non-trivial exponential-time algorithms for many hard cases.</p></div>","PeriodicalId":55586,"journal":{"name":"Autonomous Agents and Multi-Agent Systems","volume":"40 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10458-026-09753-9.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148172666","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}

{"title":"Resource allocation under the latin square constraint","authors":"Yasushi Kawase,&nbsp;Bodhayan Roy,&nbsp;Mohammad Azharuddin Sanpui","doi":"10.1007/s10458-026-09759-3","DOIUrl":"10.1007/s10458-026-09759-3","url":null,"abstract":"<div><p>A Latin square is an <span>(n times n)</span> matrix filled with <i>n</i> distinct symbols, each of which appears exactly once in each row and exactly once in each column. We introduce a problem of allocating <i>n</i> indivisible items among <i>n</i> agents over <i>n</i> rounds while satisfying the Latin square constraint. This constraint ensures that each agent receives no more than one item per round and receives each item at most once. Each agent has an additive valuation on the item–round pairs. Real-world applications like scheduling, resource management, and experimental design require the Latin square constraint to satisfy fairness or balancedness in allocation. Our goal is to find a partial or complete allocation that maximizes the sum of the agents’ valuations (utilitarian social welfare) or the minimum of the agents’ valuations (egalitarian social welfare). For the problem of maximizing utilitarian social welfare, we prove NP-hardness even when the valuations are binary and additive. We then provide <span>((1-1/e))</span> and <span>((1-1/e)/4)</span>-approximation algorithms for partial and complete settings, respectively. Additionally, we present fixed-parameter tractable (FPT) algorithms with respect to the order of Latin square and the optimum value for both partial and complete settings. For the problem of maximizing egalitarian social welfare, we establish that deciding whether the optimum value is at most 1 or at least 2 is NP-hard for both the partial and complete settings, even when the valuations are binary. Furthermore, we show that for each of the following fairness criteria—envy-free (EF), proportional (PROP), equitable (EQ), envy-free up to any good (EFX), proportional up to any good (PROPX), and equitable up to any good (EQX)—deciding whether a complete allocation satisfying that criterion exists is NP-hard, even when all agents have identical valuations.</p></div>","PeriodicalId":55586,"journal":{"name":"Autonomous Agents and Multi-Agent Systems","volume":"40 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148010069","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}

{"title":"GRAPE-S: near real-time coalition formation for multiple service collectives","authors":"Grace Diehl,&nbsp;Julie A. Adams","doi":"10.1007/s10458-026-09758-4","DOIUrl":"10.1007/s10458-026-09758-4","url":null,"abstract":"<div><p>Robotic collectives for military and disaster response applications require coalition formation algorithms to partition robots into appropriate task teams. Collectives’ missions will often incorporate tasks that require multiple high-level robot behaviors or <i>services</i>, which coalition formation must accommodate. The highly dynamic and unstructured application domains also necessitate that coalition formation algorithms produce near optimal solutions (i.e., <span>(varvec{&gt;95})</span>% utility) in near real-time (i.e., <span>(varvec{&lt;5})</span> minutes) with very large collectives (i.e., hundreds of robots). No previous coalition formation algorithm satisfies these requirements. An initial evaluation found that traditional auction-based algorithms’ runtimes are too long, even though the centralized simulator incorporated ideal conditions unlikely to occur in real-world deployments (i.e., synchronization across robots and perfect, instantaneous communication). The hedonic game-based GRAPE algorithm can produce solutions in near real-time, but cannot be applied to multiple service collectives. This manuscript integrates GRAPE and a services model, producing GRAPE-S and Pair-GRAPE-S. These algorithms and two auction baselines were evaluated using a centralized simulator with up to 1000 robots, and via the largest distributed coalition formation simulated evaluation to date, with up to 500 robots. The evaluations demonstrate that auctions transfer poorly to distributed collectives, resulting in excessive runtimes and low utility solutions. GRAPE-S satisfies the target domains’ coalition formation requirements, producing near optimal solutions in near real-time, and Pair-GRAPE-S more than satisfies the domain requirements, producing <i>optimal</i> solutions in near real-time. GRAPE-S and Pair-GRAPE-S are the first algorithms demonstrated to support near real-time coalition formation for very large, distributed collectives with multiple services.</p></div>","PeriodicalId":55586,"journal":{"name":"Autonomous Agents and Multi-Agent Systems","volume":"40 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148010068","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}