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aaai-MAKE 2023 - Proceedings of the aaai 2023 spring symposium on Challenges Requiring the Combination of Machine Learning and Knowledge Engineering

AAAI-MAKE 2023 - Proceedings of the AAAI 2023 Spring Symposi...

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aaai 2023 spring symposium on Challenges Requiring the Combination of Machine Learning and Knowledge Engineering, aaai-MAKE 2023

The proceedings contain 26 papers. The topics discussed include: a systematic and efficient approach to the design of modular hybrid ai systems;embedded to interpretive: a paradigm shift in knowledge discovery to represent dynamic knowledge;hybrid machine learning/knowledge base systems learning through natural language dialogue with deep learning models;robot behavior-tree-based task generation with large language models;an early warning system that combines machine learning and a rule-based approach for the prediction of cancer patients' unplanned visits;dynamic ontology matching challenge;ontology-driven enhancement of process mining with domain knowledge;towards hybrid dialog management strategies for a health coach chatbot;neuro-symbolic rule learning in real-world classification tasks;rule-based knowledge discovery via anomaly detection in tabular data;and leveraging RDF graphs, similarity metrics and network analysis for business process management.

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experimental design for real-world systems - papers from the aaai spring symposium

Experimental Design for Real-World Systems - Papers from the...

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experimental design for real-world systems - papers from the aaai spring symposium

ISBN: (纸本)9781577354109

The proceedings contain 8 papers. The topics discussed include: invited speakers and panelist biographies;improving robotics competitions for real-world evaluation of AI;use of large sample sizes and multiple evaluation methods in human-robot interaction experimentation;human-robot interaction studies for autonomous mobile manipulation for the motor impaired;drumming with a humanoid robot: lessons learnt from designing and analyzing human-robot interaction studies;variable body image - evaluation framework of robot's appearance using movable human-like parts;'outside-in' design for interdisciplinary HRI research;evaluating the effects of culture and etiquette on human-computer interaction and human performance;and LILAC - learn from Internet: log, annotation, and content.

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Game Theory for Security, Sustainability, and Health - papers from the aaai spring symposium

Game Theory for Security, Sustainability, and Health - Paper...

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2012 aaai spring symposium

ISBN: (纸本)9781577355526

The proceedings contain 14 papers. The topics discussed include: security games with limited surveillance: an initial report;strategy representation analysis for patrolling games;the design of computer simulation experiments of complex adaptive social systems for risk based analysis of intervention strategies;a study of phase transitions in security games;towards optimal patrol strategies for fare inspection in transit systems;challenges in patrolling to maximize pristine forest area;efficient approximation for security games with interval uncertainty;adaptive learning agents for sustainable building energy management;the challenge of flexible intelligence for models of human behavior;incentive based cooperation in multi-agent auctions;game theory for security: a real-world challenge problem for multiagent systems and beyond;extending security games to defenders with constrained mobility;and adversarial patrolling games.

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The design of computer simulation experiments of complex adaptive social systems for risk based analysis of intervention strategies

The design of computer simulation experiments of complex ada...

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2012 aaai spring symposium

作者： Duong, Deborah V. Agent Based Learning Systems United States

ISBN: (纸本)9781577355526

Computational social science, as with all complex adaptive systems sciences, involves a great amount of uncertainty on several fronts, including intrinsic arbitrariness such as that due to path dependence, disagreement on social theory and how to capture it in software, input data of different credibility that does not exactly match the requirements of software because it was gathered for another purpose, and inexactly matching translations between models that were designed for different purposes than the study at hand. This paper presents a method of formally tracking that uncertainty, keeping the data input parameters proportionate with logical and probabilistic constraints, and capturing proportionate dynamics of the output ordered by the decision points of policy change, for the purpose of risk-based analysis. Once ordered this way, the data can be compared to other data similarly expressed, whether that data is from simulation excursions or from the real world, for objective comparison and distance scoring at the level of dynamic patterns as opposed to single outcome validation. This method enables wargame adjudicators to be run out with data gleaned from the wargame, enables data to be repurposed for both training and testing set, and facilitates objective validation scoring through soft matching. Artificial intelligence tools used in the method include probabilistic ontologies with crisp and Bayesian inference, game trees that are multiplayer non-zero sum and decision point based rather than turn-based, and Markov processes to represent the dynamic data and align the models for objective comparison. Copyright © 2011, Association for the Advancement of Artificial Intelligence. All rights reserved.

关键词： Markov processes

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Propagating uncertainty in solar panel performance for life cycle modeling in early stage design

Propagating uncertainty in solar panel performance for life ...

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2011 aaai spring symposium

作者： Honda, Tomonori Chen, Heidi Q. Chan, Kennis Y. Yang, Maria C. Department of Mechanical Engineering Massachusetts Institute of Technology Cambridge MA 02139 United States ATAC Corporation Sunnyvale CA 94085 United States Department of Mechanical Engineering Engineering System Division Massachusetts Institute of Technology Cambridge MA 02139 United States

ISBN: (纸本)9781577354949

One of the challenges in accurately applying metrics for life cycle assessment lies in accounting for both irreducible and inherent uncertainties in how a design will perform under real world conditions. This paper presents a preliminary study that compares two strategies, one simulation-based and one set-based, for propagating uncertainty in a system. These strategies for uncertainty propagation are then aggregated. This work is conducted in the context of an amorphous photovoltaic (PV) panel, using data gathered from the National Solar Radiation Database, as well as realistic data collected from an experimental hardware setup specifically for this study. Results show that the influence of various sources of uncertainty can vary widely, and in particular that solar radiation intensity is a more significant source of uncertainty than the efficiency of a PV panel. This work also shows both set-based and simulation-based approaches have limitations and must be applied thoughtfully to prevent unrealistic results. Finally, it was found that aggregation of the two uncertainty propagation methods provided faster results than either method alone. Copyright © 2011, Association for the Advancement of Artificial Intelligence. All rights reserved.

关键词： Life cycle

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Outside-in design for interdisciplinary hri research

Outside-in design for interdisciplinary hri research

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experimental design for real-world systems - papers from the aaai spring symposium

作者： Šabanovic, Selma Meisner, Eric Caporael, Linnda R. Isler, Volkan Trinkle, Jeff Program in Science Technology and Society Stanford University United States Department of Computer Science Rensselaer Polytechnic Institute United States Department of Science and Technology Studies Rensselaer Polytechnic Institute United States Department of Computer Science University of Minnesota United States

ISBN: (纸本)9781577354109

This paper introduces "outside-in design" as a collaborative approach to social robot design and human-robot interaction research. As an interdisciplinary group of social and computer scientists, we follow an iterative practice of collecting and analyzing data from real-world interaction, designing appropriate robotic perception and control mechanisms, developing models of interaction through automatic coding of behaviors and evaluation by human subjects, and validating the models in embodied human-robot interaction. We apply this approach in the context of shadow puppeteering, a constrained interaction space which allows us to study the foundational elements of synchronous interaction and apply them to a robot. We contribute to both social and computer sciences by combining the study of human social interaction with the design of socially responsive robot control algorithms. © 2009, Association for the Advancement of Artificial Intelligence.

关键词： Human robot interaction

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A semantic design pattern language for complex event processing

A semantic design pattern language for complex event process...

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Intelligent Complex Event Processing - papers from the aaai spring symposium

作者： Paschke, Adrian Free Universtity Berlin Germany

ISBN: (纸本)9781577354123

Complex Event Processing (CEP) is an emerging enabling technology to achieve relevant situational knowledge from distributed systems in real-time or almost real- time. It gains more and more attention due to the industry hype and momentum regarding situation-aware computing and service-orientation. Support for CEP is considered to become a critical success factor for many businesses, especially regarding the recent failures of many industrial ventures due to insufficient situation-awareness. However, first experiences in using the CEP technology and setting up CEP applications have shown that the potential adopters have major problems in understanding and adequately designing and implementing successful CEP solutions. CEP engineering remains a laborious trial and error process with slow development and change cycles., , The purpose of this paper is to contribute with a multi-dimensional categorization of CEP (design) patterns and a semantic design pattern language to describe successful CEP designs and build up libraries of CEP best practice descriptions and CEP patterns. This will lead towards a more structured approach for the design of CEP systems and will allow for the exact characterization and comparison of a broad variety of CEP media and systems. The intention is to support an interdisciplinary and efficient communication process about design solutions for various CEP problems in order to reach a thoroughly understanding of the proposed CEP pattern approach which offers an additional increase (1) in efficiency, aimed at cheaper and faster delivery of CEP-based systems by supporting CEP system engineers in their design decisions, and (2) in reusability of successful CEP solutions to frequently occurring CEP design problems in different domains. © 2009, Association for the Advancement of Artificial Intelligence.

关键词： Reusability

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aaai spring symposium - Technical Report: Preface

AAAI Spring Symposium - Technical Report

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aaai spring symposium - Technical Report 2009年 SS-09-03卷 vii页

作者： Tsui, Katherine Feil-Seifer, David Maldonado, Heidy Mutlu, Bilge Stubbs, Kris Ten Takayama, Leila University of Massachusetts Lowell United States University of Southern California United States Stanford University United States Carnegie Mellon University United States

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Reports of the aaai 2009 spring symposia

Reports of the AAAI 2009 spring symposia

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作者： Bao, Jie Bojars, Uldis Choudhury, Tanzeem Ding, Li Greaves, Mark Kapoor, Ashish Louchart, Sandy Mehta, Manish Nebel, Bernhard Nirenburg, Sergei Oates, Tim Roberts, David L. Sanfilippo, Antonio Stojanovic, Nenad Stubbs, Kristen Thomaz, Andrea L. Tsui, Katherine Woelfl, Stefan Tetherless World Constellation Rensselaer Polytechnic Institute United States Social Software Unit of DERI Galway Ireland Computer Science Department Dartmouth College United States Knowledge Systems at Vulcan Inc United States Adaptive Systems and Interaction Group Microsoft Research Redmond United States School for Mathematics and Computer Sciences Heriot-Watt University United Kingdom School ot Interactive Computing Georgia Institute of Technology United States Department of Computer Science University of Freiburg Germany Computer Science and Electrical Engineering Department University of Maryland Baltimore County United States Pacific Northwest National Laboratory Richland WA United States University of Karlsruhe Germany IRobot Corporation United States University of Massachusetts Lowell United States

The Association for the Advancement of Artificial Intelligence, in cooperation with Stanford University's Department of Computer Science, was pleased to present the 2009 spring symposium Series, held Monday through Wednesday, March 23-25, 2009, at Stanford University. The titles of the nine symposia were Agents That Learn from Human Teachers, Benchmarking of Qualitative Spatial and Temporal Reasoning systems, experimental design for real- world systems, Human Behavior Modeling, Intelligent Event Processing, Intelligent Narrative Technologies II, Learning by Reading and Learning to Read, Social Semantic Web: Where Web 2.0 Meets Web 3.0, and Technosocial Predictive Analytics. The goal of the Agents That Learn from Human Teachers symposium was to investigate how we can enable software and robotics agents to leam from real-time interaction with an everyday human partner. The aim of the Benchmarking of Qualitative Spatial and Temporal Reasoning systems symposium was to initiate the development of a problem repository in the field of qualitative spatial and temporal reasoning and identify a graded set of challenges for future midterm and long-term research. The experimental design symposium discussed the challenges of evaluating AI systems. The Human Behavior Modeling symposium explored reasoning methods for understanding various aspects of human behavior, especially in the context of designing intelligent systems that interact with humans. The Intelligent Event Processing symposium discussed the need for more Al-based approaches in event pro-cessing and defined a kind of research agenda for the field, coined as intelligent complex event processing (iCEP). The Intelligent Narrative Technologies IIaaai symposium discussed innovations, progress, and novel techniques in the research domain. The Learning by Reading and Learning to Read symposium explored two aspects of making natural language texts semantically accessible to, and processable by, machines. The Social Semantic

关键词： Benchmarking

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Reports of the aaai 2009 spring Symposia

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AI Magazine 2009年第3期30卷 89-95页

作者： Jie Bao Uldis Bojars Tanzeem Choudhury Li Ding Mark Greaves Ashish Kapoor Sandy Louchart Manish Mehta Bernhard Nebel Sergei Nirenburg Tim Oates David L. Roberts Antonio Sanfilippo Nenad Stojanovic Kristen Stubbs Andrea L. Thomaz Katherine Tsui Stefan Woelfl

The Association for the Advancement of Artificial Intelligence, in cooperation with Stanford University's Department of Computer Science, was pleased to present the 2009 spring symposium Series, held Monday through Wednesday, March 23-25, 2009, at Stanford University. The titles of the nine symposia were Agents That Learn from Human Teachers, Benchmarking of Qualitative Spatial and Temporal Reasoning systems, experimental design for real-world systems, Human Behavior Modeling, Intelligent Event Processing, Intelligent Narrative Technologies II, Learning by Reading and Learning to Read, Social Semantic Web: Where Web 2.0 Meets Web 3.0, and Technosocial Predictive Analytics. The goal of the Agents That Learn from Human Teachers symposium was to investigate how we can enable software and robotics agents to learn from real-time interaction with an everyday human partner. The aim of the Benchmarking of Qualitative Spatial and Temporal Reasoning systems symposium was to initiate the development of a problem repository in the field of qualitative spatial and temporal reasoning and identify a graded set of challenges for future midterm and long-term research. The experimental design symposium discussed the challenges of evaluating AI systems. The Human Behavior Modeling symposium explored reasoning methods for understanding various aspects of human behavior, especially in the context of designing intelligent systems that interact with humans. The Intelligent Event Processing symposium discussed the need for more AI-based approaches in event processing and defined a kind of research agenda for the field, coined as intelligent complex event processing (iCEP). The Intelligent Narrative Technologies II aaai symposium discussed innovations, progress, and novel techniques in the research domain. The Learning by Reading and Learning to Read symposium explored two aspects of making natural language texts semantically accessible to, and processable by, machines. The Social Semantic

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