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ORCIDAAAI Spring Symposia 2018: Palo Alto, CA, USA
- 2018 AAAI Spring Symposia, Stanford University, Palo Alto, California, USA, March 26-28, 2018. AAAI Press 2018
AI and Society: Ethics, Safety and Trustworthiness in Intelligent Agents
- Oliver Bendel:
From GOODBOT to BESTBOT. - Oliver Bendel:
The Uncanny Return of Physiognomy. - Umang Bhatt:
Maintaining the Humanity of Our Models. - Emanuelle Burton, Kristel Clayville, Judy Goldsmith, Nicholas Mattei:
The Heart of the Matter: Patient Autonomy as a Model for the Wellbeing of Technology Users. - Stefania Costantini, Giovanni De Gasperis, Abeer Dyoub, Valentina Pitoni:
Trustworthiness and Safety for Intelligent Ethical Logical Agents via Interval Temporal Logic and Runtime Self-Checking. - Kyle Dent:
Ethical Considerations for AI Researchers. - Piotr J. Gmytrasiewicz, George Moe, Adolfo Moreno:
Interactive Agent that Understands the User. - Philip C. Jackson Jr.:
Toward Beneficial Human-Level AI... and Beyond. - Andrea Loreggia, Nicholas Mattei, Francesca Rossi, Kristen Brent Venable:
Preferences and Ethical Principles in Decision Making. - Rafal Rzepka, Kenji Araki:
Importance of Contextual Knowledge in Artificial Moral Agents Development. - Nolan P. Shaw, Andreas Stöckel, Ryan W. Orr, Thomas Finn Lidbetter, Robin Cohen:
Towards Provably Moral AI Agents in Bottom-Up Learning Frameworks. - Dan Ventura:
Ethics as Aesthetic for Artificial General Intelligence. - Yetian Wang, Daniel Friyia, Kanzhe Liu, Robin Cohen:
An Architecture for a Military AI System with Ethical Rules. - Mark R. Waser, David J. Kelley:
Architecting a Human-Like Emotion-Driven Conscious Moral Mind for Value Alignment and AGI Safety. - Patti West-Smith, Stephanie Butler, Elijah Mayfield:
Trustworthy Automated Essay Scoring without Explicit Construct Validity. - Andrew B. Williams:
The Potential Social Impact of the Artificial Intelligence Divide.
Artificial Intelligence for the Internet of Everything
- Spencer Breiner, Ram D. Sriram, Eswaran Subrahmanian:
Compositional Models for the Internet of Everything. - Kai Chih Chang, Razieh Nokhbeh Zaeem, K. Suzanne Barber:
Internet of Things: Securing the Identity by Analyzing Ecosystem Models of Devices and Organizations. - Hesham Fouad, Ira S. Moskowitz:
Meta-Agents: Managing Dynamism in the Internet of Things (IoT) with Multi-agent Networks. - Boris A. Galitsky:
Message Validation Pipeline for Agents of the Internet of Everything. - Barry M. Horowitz:
Policy Issues Regarding Implementations of Cyber Attack Resilience Solutions for Cyber Physical Systems. - Brian Jalaian, Alec Koppel, Andre V. Harrison, James Michaelis, Stephen Russell:
On Stream-Centric Learning for Internet of Battlefield Things. - Alexander Kott:
Challenges and Characteristics of Intelligent Autonomy for Internet of Battle Things in Highly Adversarial Environments. - William F. Lawless, Ranjeev Mittu, Donald A. Sofge:
Artificial Intelligence for the Internet of Everything. - Georgiy Levchuk, Krishna R. Pattipati, Adam Fouse, Robert McCormack, Daniel Serfaty:
Active Inference in Multi-Agent Systems: Context-Driven Collaboration and Decentralized Purpose-Driven Team Adaptation. - Joseph B. Lyons, Sean Mahoney, Kevin T. Wynne, Mark A. Roebke:
Viewing Machines as Teammates: A Qualitative Study. - Ira S. Moskowitz, Stephen Russell:
Valuable Information and the Internet of Things. - Michael Mylrea:
AI Enabled Blockchain Smart Contracts: Cyber Resilient Energy Infrastructure and IoT. - Magnus Sahlgren, Erik Ylipää, Barry A. T. Brown, Karey Helms, Airi Lampinen, Donald McMillan, Jussi Karlgren:
The Smart Data Layer. - Michael Wollowski, John McDonald, Vishal Kapashi, Benjamin Chodroff:
The Web of Smart Entities - Towards a Theory of the Next Generation of the Internet of Things.
Beyond Machine Intelligence: Understanding Cognitive Bias and Humanity for Well-Being AI
- Saleh Ahmed, Mahboob Qaosar, Rizka Wakhidatus Sholikah, Yasuhiko Morimoto:
Early Dementia Detection through Conversations to Virtual Personal Assistant. - Christina Alexandris:
Measuring Cognitive Bias in Spoken Interaction and Conversation. - Sachiko Deguchi:
A Study on the UI of Musical Performance System and Score Representation. - Amy Wenxuan Ding:
A Dynamic Learning Model for a Better Personalized Healthcare Using Mobile Health Tools. - Boris Galitsky:
Customers' Retention Requires an Explainability Feature in Machine Learning Systems They Use. - Teruaki Hayashi, Yukio Ohsawa:
Retrieval System for Data Utilization Knowledge Integrating Stakeholders' Interests. - Ayae Ide, Yoichi Motomura, Takao Terano:
Policy Decision Support System in Aging Society Based on Probabilistic Latent Spatial Semantic Structure Modeling. - Tomohiko Inazumi, Jinhwan Kwon, Shinsaku Hiura, Maki Sakamoto:
Texture Suggestion System Considering the Elderly's Preference on 3D Printing. - Takashi Kido, Keiki Takadama:
The Challenges for Understanding Cognitive Bias and Humanity for Well-Being AI - Beyond Machine Intelligence. - John Licato, Mark Boger, Zhitian Zhang:
Developing a Dataset for Personal Attacks and Other Indicators of Biases. - Yunshi Liu, Pujana Paliyawan, Takahiro Kusano, Tomohiro Harada, Ruck Thawonmas:
A Personalized Method for Calorie Consumption Assessment. - Shintaro Nagama, Masayuki Numao:
IoT-based Emotion Recognition Robot to Enhance Sense of Community in Nursing Home. - Nobuyuki Oishi, Masayuki Numao:
Active Online Learning Architecture for Multimodal Sensor-based ADL Recognition. - Mihoko Otake, Masato S. Abe, Masahiro Nochi, Eij Shimizu:
Estimation of Personalized Value through the Analysis of Conversational Data Assisted by Coimagination Method. - Mahboob Qaosar, Saleh Ahmed, Chen Li
, Yasuhiko Morimoto:
Hybrid Sensing and Wearable Smart Device for Health Monitoring and Medication: Opportunities and Challenges. - Sadeq Rahimi:
From Algorithms to Heuristics: Will Androids Ever Make Freudian Slips? - Yusuke Tajima, Akinori Murata, Tomohiro Harada, Keiki Takadama:
Sleep Stage Re-Estimation Method According To Sleep Cycle Change. - Keiki Takadama:
Can Machine Learning Correct Commonly Accepted Knowledge and Provide Understandable Knowledge in Care Support Domain? Tackling Cognitive Bias and Humanity from Machine Learning Perspective. - Ryo Takano, Satoshi Hasegawa, Yuta Umenai, Takato Tatsumi, Keiki Takadama, Toru Shimuta, Toru Yabe, Hideo Matsumoto:
Study of Analytical Methods on the Relationship between Sleep Quality and Stress with a focus on Human Circadian Rhythm. - Akari Tobaru, Fumito Uwano, Takuya Iwase, Kazuma Matsumoto, Ryo Takano, Yusuke Tajima, Yuta Umenai, Keiki Takadama:
Improving Sleep Stage Estimation Accuracy by Circadian Rhythm Extracted from a Low Frequency Component of Heart Rate. - Fumito Uwano, Keiki Takadama:
Ensemble Heart Rate Extraction Method for Biological Data from Water Pressure Sensor. - Hideya Yamamoto, Kaoru Ito, Chihiro Honda, Eiji Aramaki:
Does Digital Dementia Exist?
Data Efficient Reinforcement Learning
- Majid Alkaee Taleghan, Thomas G. Dietterich:
Efficient Exploration for Constrained MDPs. - Josiah P. Hanna, Peter Stone:
Towards a Data Efficient Off-Policy Policy Gradient. - Heejin Jeong, Daniel D. Lee:
Bayesian Q-learning with Assumed Density Filtering. - Jacob Menashe, Peter Stone:
State Abstraction Synthesis for Discrete Models of Continuous Domains. - Mikhail Pavlov, Sergey Kolesnikov, Sergey M. Plis:
Run, Skeleton, Run: Skeletal Model in a Physics-Based Simulation. - Adrian Sosic, Abdelhak M. Zoubir, Heinz Koeppl:
Inverse Reinforcement Learning via Nonparametric Subgoal Modeling. - Ermo Wei, Drew Wicke, David Freelan, Sean Luke:
Multiagent Soft Q-Learning. - Ermo Wei, Drew Wicke, Sean Luke:
Hierarchical Approaches for Reinforcement Learning in Parameterized Action Space.
The Design of the User Experience for Artificial Intelligence (the UX of AI)
- Dorrit Billman, Debra Schreckenghost:
Usability Issues and Guidance for Flexible Execution of Procedural Work. - Johanne Christensen, Benjamin Watson, A. J. Rindos, Stacy Joines:
Building Bridges: A Case Study in Structuring Human-ML Training Interactions via UX. - Richard G. Freedman, Tathagata Chakraborti, Kartik Talamadupula, Daniele Magazzeni, Jeremy D. Frank:
User Interfaces and Scheduling and Planning: Workshop Summary and Proposed Challenges. - Fabien Girardin, Pablo Fleurquin:
Designing for Trust with Machine Learning. - Nick Gisolfi, Artur Dubrawski:
Revealing Actionable Simplicity in Data. - Kuldeep Gohel:
Artificial Digitality. - Erik Harpstead, Christopher J. MacLellan, Robert P. Marinier, Kenneth R. Koedinger:
Towards Natural Cognitive System Training Interactions: A Preliminary Framework. - Karey Helms, Barry A. T. Brown, Magnus Sahlgren, Airi Lampinen:
Design Methods to Investigate User Experiences of Artificial Intelligence. - Aisling Kelliher, Barbara Barry:
Designing Therapeutic Care Experiences with AI in Mind. - Yeawon Kim:
Insectile Indices. - Martin Lindvall, Jesper Molin, Jonas Löwgren:
The Importance of UX for Machine Teaching. - Xiaoxuan Liu, Godiva Veliganilao Reisenbichler:
Trees of Knowledge: Designing with Artificial Intelligence in the Urban Landscape. - Josh Lovejoy:
The UX of AI: Using Google Clips to Understand how a Human-Centered Design Process Elevates Artificial Intelligence. - Betti Marenko:
FutureCrafting. A Speculative Method for an Imaginative AI. - Nikolas Martelaro, Wendy Ju:
A Panel on Cybernetics and the User Experience of AI Systems. - Christine Meinders, Selwa Sweidan:
Knowledge Design - Towards an Inclusive, AI Design Practice. - Sarah Mennicken, Ruth Brillman, Jennifer Thom, Henriette Cramer:
Challenges and Methods in Design of Domain-specific Voice Assistants. - Michael Milano:
Intelligent Devices Retirement Preserve: (un) Natural Wonders. - Afshin Mobramaein, Jim Whitehead, Chandranil Chakraborttii:
Talk to Me About Pong: On Using Conversational Interfaces for Mixed-Initiative Game Design. - Johnathan Pagnutti:
How Can I Cook with This: User Experience Challenges for AI in the Home Kitchen. - Debra Schreckenghost, Scott Bell, David Kortenkamp, James Kramer:
Procedure Automation: Sharing Work with Users. - Aaron Springer, Jean Garcia-Gathright, Henriette Cramer:
Assessing and Addressing Algorithmic Bias - But Before We Get There... - Aaron Springer, Steve Whittaker:
What Are You Hiding? Algorithmic Transparency and User Perceptions. - Janice Y. Tsai, Jofish Kaye:
Hey Scout: Designing a Browser-Based Voice Assistant. - Jason Wong:
Committee of Infrastructure: Civic Agency and Representation. - Qian Yang:
Machine Learning as a UX Design Material: How Can We Imagine Beyond Automation, Recommenders, and Reminders?
Integrating Representation, Reasoning, Learning, and Execution for Goal Directed Autonomy
- Saeid Amiri, Suhua Wei, Shiqi Zhang, Jivko Sinapov, Jesse Thomason, Peter Stone:
Robot Behavioral Exploration and Multi-modal Perception using Dynamically Constructed Controllers. - Roman Barták, Adrien Maillard, Rafael Cauê Cardoso:
Validation of Hierarchical Plans via Parsing of Attribute Grammars. - Michael Cashmore, Andrew Coles, Bence Cserna, Erez Karpas, Daniele Magazzeni, Wheeler Ruml:
Situated Planning for Execution Under Temporal Constraints. - Dongkyu Choi, Pat Langley, Son Thanh To:
Creating and Using Tools in a Hybrid Cognitive Architecture. - Stefania Costantini, Giovanni De Gasperis:
Flexible Goal-Directed Agents' Behavior via DALI MASs and ASP Modules. - Werner Damm, Martin Fränzle, Sebastian Gerwinn, Paul Kröger:
Perspectives on the Validation and Verification of Machine Learning Systems in the Context of Highly Automated Vehicles. - Angel Andres Daruna, Vivian Chu, Weiyu Liu, Meera Hahn, Priyanka Khante, Sonia Chernova, Andrea Thomaz:
SiRoK: Situated Robot Knowledge - Understanding the Balance Between Situated Knowledge and Variability. - Tuan Do, Nikhil Krishnaswamy, James Pustejovsky:
Teaching Virtual Agents to Perform Complex Spatial-Temporal Activities. - Nakul Gopalan:
Planning Hierarchies and their Connections to Language. - Edward Groshev, Aviv Tamar, Maxwell Goldstein, Siddharth Srivastava, Pieter Abbeel:
Learning Generalized Reactive Policies using Deep Neural Networks. - Till Hofmann, Victor Mataré, Stefan Schiffer, Alexander Ferrein, Gerhard Lakemeyer:
Constraint-Based Online Transformation of Abstract Plans into Executable Robot Actions. - Chen Huang, Lantao Liu, Gaurav S. Sukhatme:
Learning to Act in Partially Structured Dynamic Environment. - Pat Langley, Mohan Sridharan, Ben Meadows:
Representation, Use, and Acquisition of Affordances in Cognitive Systems. - David H. Ménager, Dongkyu Choi, Mark Roberts, David W. Aha:
Learning Planning Operators from Episodic Traces. - Matthew Molineaux, Michael W. Floyd, Dustin Dannenhauer, David W. Aha:
Human-Agent Teaming as a Common Problem for Goal Reasoning. - Kyle John Morris, John Anderson, Meng Cheng Lau, Jacky Baltes:
Interaction and Learning in a Humanoid Robot Magic Performance. - Alexander Shleyfman, Erez Karpas:
Position Paper: Reasoning About Domains with PDDL. - Biplav Srivastava:
On Chatbots Exhibiting Goal-Directed Autonomy in Dynamic Environments. - Siddharth Srivastava:
Safe Goal-Directed Autonomy and the Need for Sound Abstractions. - Einoshin Suzuki:
Exploiting Micro-Clusters to Close The Loop in Data-Mining Robots for Human Monitoring. - Lawson L. S. Wong:
Learning Abstractions by Transferring Abstract Policies to Grounded State Spaces. - Shaojun Zhu, David Allen Surovik, Kostas E. Bekris, Abdeslam Boularias:
Information-Efficient Model Identification for Tensegrity Robot Locomotion.
Learning, Inference, and Control of Multi-Agent Systems
- Magnus Boman, Magnus Sahlgren, Olof Görnerup, Daniel Gillblad:
Learning Machines. - Panayiotis Danassis, Boi Faltings:
Learning in Ad-hoc Anti-coordination Scenarios. - Richard Everett, Stephen J. Roberts:
Learning Against Non-Stationary Agents with Opponent Modelling and Deep Reinforcement Learning. - Sam Ganzfried, Qingyun Sun:
Bayesian Opponent Exploitation in Imperfect-Information Games. - Yanlin Han, Piotr J. Gmytrasiewicz:
Learning Others' Intentional Models in Multi-Agent Settings Using Interactive POMDPs. - Richard Klíma, Karl Tuyls, Frans A. Oliehoek:
Model-Based Reinforcement Learning under Periodical Observability. - Alexander Peysakhovich, Adam Lerer:
Towards AI that Can Solve Social Dilemmas. - William G. Squires, Sean Luke:
LfD Training of Heterogeneous Formation Behaviors.
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