Annals of Mathematics and Artificial Intelligence最新文献

Common equivalence and size of forgetting from Horn formulae

IF 1.2 4区计算机科学

Annals of Mathematics and Artificial Intelligence Pub Date : 2024-10-29 DOI: 10.1007/s10472-024-09955-5

Paolo Liberatore

引用次数: 0

Time-penalised trees (TpT): introducing a new tree-based data mining algorithm for time-varying covariates 时变树（TpT）：为时变协变量引入一种新的基于树的数据挖掘算法

IF 1.2 4区计算机科学

Annals of Mathematics and Artificial Intelligence Pub Date : 2024-08-22 DOI: 10.1007/s10472-024-09950-w

Mathias Valla

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引用次数: 0

Conformal test martingales for hypergraphical models 超图模型的共形检验马氏体

IF 1.2 4区计算机科学

Annals of Mathematics and Artificial Intelligence Pub Date : 2024-08-03 DOI: 10.1007/s10472-024-09951-9

Ilia Nouretdinov

引用次数: 0

Advances in preference handling: foreword 偏好处理的进展：前言

IF 1.2 4区计算机科学

Annals of Mathematics and Artificial Intelligence Pub Date : 2024-07-27 DOI: 10.1007/s10472-024-09954-6

Khaled Belahcène, Sébastien Destercke, Christophe Labreuche, Meltem Öztürk, Paolo Viappiani

引用次数: 0

Costly information providing in binary contests 在二进制竞赛中提供昂贵的信息

IF 1.2 4区计算机科学

Annals of Mathematics and Artificial Intelligence Pub Date : 2024-07-27 DOI: 10.1007/s10472-024-09953-7

Noam Simon, Priel Levy, David Sarne

{"title":"Costly information providing in binary contests","authors":"Noam Simon, Priel Levy, David Sarne","doi":"10.1007/s10472-024-09953-7","DOIUrl":"10.1007/s10472-024-09953-7","url":null,"abstract":"<div><p>Contests are commonly used as a mechanism for eliciting effort and participation in multi-agent settings. Naturally, and much like with various other mechanisms, the information provided to the agents prior to and throughout the contest fundamentally influences its outcomes. In this paper we study the problem of information providing whenever the contest organizer does not initially hold the information and obtaining it is potentially costly. As the underlying contest mechanism for our model we use the binary contest, where contestants’ strategy is captured by their decision whether or not to participate in the contest in the first place. Here, it is often the case that the contest organizer can proactively obtain and provide contestants information related to their expected performance in the contest. We provide a comprehensive equilibrium analysis of the model, showing that even when such information is costless, it is not necessarily the case that the contest organizer will prefer to obtain and provide it to all agents, let alone when the information is costly.</p></div>","PeriodicalId":7971,"journal":{"name":"Annals of Mathematics and Artificial Intelligence","volume":"92 5","pages":"1353 - 1375"},"PeriodicalIF":1.2,"publicationDate":"2024-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10472-024-09953-7.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141779355","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Tumato 2.0 - a constraint-based planning approach for safe and robust robot behavior Tumato 2.0--一种基于约束的规划方法，可实现安全、稳健的机器人行为

IF 1.2 4区计算机科学

Annals of Mathematics and Artificial Intelligence Pub Date : 2024-07-26 DOI: 10.1007/s10472-024-09949-3

Jan Vermaelen, Tom Holvoet

{"title":"Tumato 2.0 - a constraint-based planning approach for safe and robust robot behavior","authors":"Jan Vermaelen, Tom Holvoet","doi":"10.1007/s10472-024-09949-3","DOIUrl":"https://doi.org/10.1007/s10472-024-09949-3","url":null,"abstract":"<p>Ensuring the safe and effective operation of autonomous systems is a complex undertaking that inherently relies on underlying decision-making processes. To rigorously analyze these processes, formal verification methods, such as model checking, offer a valuable means. However, the non-deterministic nature of realistic environments makes these approaches challenging and often impractical. This work explores the capabilities of a constraint-based planning approach, Tumato, in generating policies that guide the system to predefined goals while adhering to safety constraints. Constraint-based planning approaches are inherently able to provide guarantees of soundness and completeness. Our primary contribution lies in extending Tumato’s capabilities to accommodate non-deterministic outcomes of actions, enhancing the robustness of the behavior. Originally designed to accommodate only deterministic outcomes, actions can now be modeled to include alternative outcomes to address contingencies explicitly. The adapted solver generates policies that enable reaching the goals in a safe manner, even when such alternative outcomes of actions occur. Additionally, we introduce a purely declarative manner for specifying safety in Tumato to further enhance its expressiveness as well as to reduce the susceptibility to errors during specification. The incorporation of cost or duration values to actions enables the solver to restore safety in the most preferred manner when necessary. Finally, we highlight the overlap of Tumato’s safety-related capabilities with a systems-theoretic approach, STPA (Systems-Theoretic Process Analysis). The aim is to emphasize the ability to avoid unsafe control actions without their explicit identification, contributing to a more comprehensive and holistic understanding of safety.</p>","PeriodicalId":7971,"journal":{"name":"Annals of Mathematics and Artificial Intelligence","volume":"44 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141779357","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Calibration methods in imbalanced binary classification 不平衡二元分类中的校准方法

IF 1.2 4区计算机科学

Annals of Mathematics and Artificial Intelligence Pub Date : 2024-07-19 DOI: 10.1007/s10472-024-09952-8

Théo Guilbert, Olivier Caelen, Andrei Chirita, Marco Saerens

引用次数: 0

Domain independent heuristics for online stochastic contingent planning 在线随机应急规划的领域独立启发式方法

IF 1.2 4区计算机科学

Annals of Mathematics and Artificial Intelligence Pub Date : 2024-07-08 DOI: 10.1007/s10472-024-09947-5

Oded Blumenthal, Guy Shani

引用次数: 0

Solving morphological analogies: from retrieval to generation 解决形态类比问题：从检索到生成

IF 1.2 4区计算机科学

Annals of Mathematics and Artificial Intelligence Pub Date : 2024-06-11 DOI: 10.1007/s10472-024-09945-7

Esteban Marquer, Miguel Couceiro

{"title":"Solving morphological analogies: from retrieval to generation","authors":"Esteban Marquer, Miguel Couceiro","doi":"10.1007/s10472-024-09945-7","DOIUrl":"https://doi.org/10.1007/s10472-024-09945-7","url":null,"abstract":"<p>Analogical inference is a remarkable capability of human reasoning, and has been used to solve hard reasoning tasks. Analogy based reasoning (AR) has gained increasing interest from the artificial intelligence community and has shown its potential in multiple machine learning tasks such as classification, decision making and recommendation with competitive results. We propose a deep learning (DL) framework to address and tackle two key tasks in AR: analogy detection and solving. The framework is thoroughly tested on the Siganalogies dataset of morphological analogical proportions (APs) between words, and shown to outperform symbolic approaches in many languages. Previous work have explored the behavior of the Analogy Neural Network for classification (ANNc) on analogy detection and of the Analogy Neural Network for retrieval (ANNr) on analogy solving by retrieval, as well as the potential of an autoencoder (AE) for analogy solving by generating the solution word. In this article we summarize these findings and we extend them by combining ANNr and the AE embedding model, and checking the performance of ANNc as an retrieval method. The combination of ANNr and AE outperforms the other approaches in almost all cases, and ANNc as a retrieval method achieves competitive or better performance than 3CosMul. We conclude with general guidelines on using our framework to tackle APs with DL.</p>","PeriodicalId":7971,"journal":{"name":"Annals of Mathematics and Artificial Intelligence","volume":"33 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141501446","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Introduction to the special issue: selected papers from EMAS 2022 特刊导言：《2022 年教育管理和服务计划》论文选

IF 1.2 4区计算机科学

Annals of Mathematics and Artificial Intelligence Pub Date : 2024-06-10 DOI: 10.1007/s10472-024-09946-6

Amit K. Chopra, Jürgen Dix, Rym Zalila-Wenkstern

引用次数: 0