Proceedings of the ... International Joint Conference on Autonomous Agents and Multiagent Systems : AAMAS. International Joint Conference on Autonomous Agents and Multiagent Systems最新文献
Eura Nofshin, Siddharth Swaroop, Weiwei Pan, Susan Murphy, Finale Doshi-Velez
{"title":"Reinforcement Learning Interventions on Boundedly Rational Human Agents in Frictionful Tasks.","authors":"Eura Nofshin, Siddharth Swaroop, Weiwei Pan, Susan Murphy, Finale Doshi-Velez","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Many important behavior changes are <i>frictionful</i>; they require individuals to expend effort over a long period with little immediate gratification. Here, an artificial intelligence (AI) agent can provide personalized interventions to help individuals stick to their goals. In these settings, the AI agent must personalize <i>rapidly</i> (before the individual disengages) and <i>interpretably</i>, to help us understand the behavioral interventions. In this paper, we introduce Behavior Model Reinforcement Learning (BMRL), a framework in which an AI agent intervenes on the parameters of a Markov Decision Process (MDP) belonging to a <i>boundedly rational human agent</i>. Our formulation of the human decision-maker as a planning agent allows us to attribute undesirable human policies (ones that do not lead to the goal) to their maladapted MDP parameters, such as an extremely low discount factor. Furthermore, we propose a class of tractable human models that captures fundamental behaviors in frictionful tasks. Introducing a notion of <i>MDP equivalence</i> specific to BMRL, we theoretically and empirically show that AI planning with our human models can lead to helpful policies on a wide range of more complex, ground-truth humans.</p>","PeriodicalId":93357,"journal":{"name":"Proceedings of the ... International Joint Conference on Autonomous Agents and Multiagent Systems : AAMAS. International Joint Conference on Autonomous Agents and Multiagent Systems","volume":"2024 ","pages":"1482-1491"},"PeriodicalIF":0.0,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11460771/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142395887","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"An Active Learning Method for the Comparison of Agent-based Models.","authors":"Swapna Thorve, Zhihao Hu, Kiran Lakkaraju, Joshua Letchford, Anil Vullikanti, Achla Marathe, Samarth Swarup","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>We develop a methodology for comparing two or more agent-based models that are developed for the same domain, but may differ in the particular data sets (e.g., geographical regions) to which they are applied, and in the structure of the model. Our approach is to learn a response surface in the common parameter space of the models and compare the regions corresponding to qualitatively different behaviors in the models. As an example, we develop an active learning algorithm to learn phase transition boundaries in contagion processes in order to compare two agent-based models of rooftop solar panel adoption.</p>","PeriodicalId":93357,"journal":{"name":"Proceedings of the ... International Joint Conference on Autonomous Agents and Multiagent Systems : AAMAS. International Joint Conference on Autonomous Agents and Multiagent Systems","volume":"2020 ","pages":"1377-1385"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8302187/pdf/nihms-1639215.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39223535","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Finding Spatial Clusters Susceptible to Epidemic Outbreaks due to Undervaccination.","authors":"Jose Cadena, Achla Marathe, Anil Vullikanti","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Geographical clusters of undervaccinated populations have emerged in various parts of the United States in recent years. Public health response involves surveillance and field work, which is very resource intensive. Given that public health resources are often limited, identifying and rank-ordering critical clusters can help prioritize and allocate scarce resources for surveillance and quick intervention. We quantify the criticality of a cluster as the additional number of infections caused if the cluster is underimmunized. We focus on finding clusters that maximize this measure and develop efficient approximation algorithms for finding critical clusters by exploiting structural properties of the problem. Our methods involve solving a more general problem of maximizing a submodular function on a graph with connectivity constraints. We apply our methods to the state of Minnesota, where we find clusters with significantly higher criticality than those obtained by heuristics used in public health.</p>","PeriodicalId":93357,"journal":{"name":"Proceedings of the ... International Joint Conference on Autonomous Agents and Multiagent Systems : AAMAS. International Joint Conference on Autonomous Agents and Multiagent Systems","volume":"2020 ","pages":"1786-1788"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8300049/pdf/nihms-1639096.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39223536","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Theoretical Background","authors":"M. Mahmoud","doi":"10.1201/9780429289613-2","DOIUrl":"https://doi.org/10.1201/9780429289613-2","url":null,"abstract":"","PeriodicalId":93357,"journal":{"name":"Proceedings of the ... International Joint Conference on Autonomous Agents and Multiagent Systems : AAMAS. International Joint Conference on Autonomous Agents and Multiagent Systems","volume":"32 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89576450","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Meghendra Singh, Achla Marathe, Madhav V Marathe, Samarth Swarup
{"title":"Behavior Model Calibration for Epidemic Simulations.","authors":"Meghendra Singh, Achla Marathe, Madhav V Marathe, Samarth Swarup","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Computational epidemiologists frequently employ large-scale agent-based simulations of human populations to study disease outbreaks and assess intervention strategies. The agents used in such simulations rarely capture the real-world decision-making of human beings. An absence of realistic agent behavior can undermine the reliability of insights generated by such simulations and might make them ill-suited for informing public health policies. In this paper, we address this problem by developing a methodology to create and calibrate an agent decision making model for a large multi-agent simulation, using survey data. Our method optimizes a cost vector associated with the various behaviors to match the behavior distributions observed in a detailed survey of human behaviors during influenza outbreaks. Our approach is a data-driven way of incorporating decision making for agents in large-scale epidemic simulations.</p>","PeriodicalId":93357,"journal":{"name":"Proceedings of the ... International Joint Conference on Autonomous Agents and Multiagent Systems : AAMAS. International Joint Conference on Autonomous Agents and Multiagent Systems","volume":"2018 ","pages":"1640-1648"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8300053/pdf/nihms-1639222.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39223534","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"An Anti-attack Model for Centralized C2C Reputation Evaluation Agent","authors":"Shujuan Ji, Baohua Liu, Benfa Zou, Chun-jin Zhang","doi":"10.1109/ICA.2016.023","DOIUrl":"https://doi.org/10.1109/ICA.2016.023","url":null,"abstract":"","PeriodicalId":93357,"journal":{"name":"Proceedings of the ... International Joint Conference on Autonomous Agents and Multiagent Systems : AAMAS. International Joint Conference on Autonomous Agents and Multiagent Systems","volume":"24 1","pages":"63-69"},"PeriodicalIF":0.0,"publicationDate":"2016-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86020650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Unifying Control in a Layered Agent Architecture","authors":"K. Fischer, J. Müller, M. Pischel","doi":"10.22028/D291-25052","DOIUrl":"https://doi.org/10.22028/D291-25052","url":null,"abstract":"In this paper, we set up a unifying perspective of the individual control layers of the architecture InteRRaP for autonomous interacting agents. InteRRaP is a pragmatic approach to designing complex dynamic agent societies, e.g. for robotics Muller & Pischel and cooperative scheduling applications Fischer et al.94. It is based on three general functions describing how the actions an agent commits to are derived from its perception and from its mental model: belief revision and abstraction, situation recognition and goal activation, and planning and scheduling. It is argued that each InteRRaP control layer - the behaviour-based layer, the local planning layer, and the cooperative planning layer - can be described by a combination of different instantiations of these control functions. The basic structure of a control layer is defined. The individual functions and their implementation in the different layers are outlined. We demonstrate various options for the design of interacting agents within this framework by means of an interacting robots application. The performance of different agent types in a multiagent environment is empirically evaluated by a series of experiments.","PeriodicalId":93357,"journal":{"name":"Proceedings of the ... International Joint Conference on Autonomous Agents and Multiagent Systems : AAMAS. International Joint Conference on Autonomous Agents and Multiagent Systems","volume":"11 1","pages":"446"},"PeriodicalIF":0.0,"publicationDate":"2011-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87971255","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Spike Detection and Sorting: Combining Algebraic Differentiations with ICA","authors":"Z. Tiganj, M. Mboup","doi":"10.1007/978-3-642-00599-2_60","DOIUrl":"https://doi.org/10.1007/978-3-642-00599-2_60","url":null,"abstract":"","PeriodicalId":93357,"journal":{"name":"Proceedings of the ... International Joint Conference on Autonomous Agents and Multiagent Systems : AAMAS. International Joint Conference on Autonomous Agents and Multiagent Systems","volume":"334 1","pages":"475-482"},"PeriodicalIF":0.0,"publicationDate":"2009-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74082391","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Estimating Phase Linearity in the Frequency-Domain ICA Demixing Matrix","authors":"Keisuke Toyama, Mark D. Plumbley","doi":"10.1007/978-3-642-00599-2_46","DOIUrl":"https://doi.org/10.1007/978-3-642-00599-2_46","url":null,"abstract":"","PeriodicalId":93357,"journal":{"name":"Proceedings of the ... International Joint Conference on Autonomous Agents and Multiagent Systems : AAMAS. International Joint Conference on Autonomous Agents and Multiagent Systems","volume":"51 1","pages":"362-370"},"PeriodicalIF":0.0,"publicationDate":"2009-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74558912","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
B. Cheon, Yong-Wan Roh, Dong-Ju Kim, Kwang-seok Hong
{"title":"An Implementation of Floral Scent Recognition System Using ICA Combined with Correlation Coefficients","authors":"B. Cheon, Yong-Wan Roh, Dong-Ju Kim, Kwang-seok Hong","doi":"10.1007/978-3-642-00599-2_82","DOIUrl":"https://doi.org/10.1007/978-3-642-00599-2_82","url":null,"abstract":"","PeriodicalId":93357,"journal":{"name":"Proceedings of the ... International Joint Conference on Autonomous Agents and Multiagent Systems : AAMAS. International Joint Conference on Autonomous Agents and Multiagent Systems","volume":"447 1","pages":"654-661"},"PeriodicalIF":0.0,"publicationDate":"2009-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77517060","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}