Direction: Human-AI Collaboration and Decision Support

Decision Optimization and Reinforcement Learning Understanding

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2024

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helpResearch questionDecision Optimization and Reinforcement Learning Understanding

How can reinforcement learning optimize users' attention switching in multitasking environments?

UIST '24AITentive: A Toolkit to Develop Reinforcement Learning-based Attention Management Systems

helpResearch questionDecision Optimization and Reinforcement Learning Understanding

How does AITentive simplify the design and development of attention management systems (AMS)?

UIST '24AITentive: A Toolkit to Develop Reinforcement Learning-based Attention Management Systems

helpResearch questionDecision Optimization and Reinforcement Learning Understanding

Can AITentive effectively support multi-scenario AMS development and improve multitasking performance?

UIST '24AITentive: A Toolkit to Develop Reinforcement Learning-based Attention Management Systems

lightbulbPractical problemDecision Optimization and Reinforcement Learning Understanding

Users frequently switching attention during multitasking achieve low efficiency, reducing productivity.

UIST '24AITentive: A Toolkit to Develop Reinforcement Learning-based Attention Management Systems

helpResearch questionDecision Optimization and Reinforcement Learning Understanding

How can natural language enhance video camera interaction capabilities to customize tasks based on user interests?

UbiComp '24ChatCam: Embracing LLMs for Contextual Chatting-to-Camera with Interest-Oriented Video Summarization

helpResearch questionDecision Optimization and Reinforcement Learning Understanding

How can multimodal language models generate lightweight task models to meet user needs in edge computing environments?

UbiComp '24ChatCam: Embracing LLMs for Contextual Chatting-to-Camera with Interest-Oriented Video Summarization

helpResearch questionDecision Optimization and Reinforcement Learning Understanding

How can deep reinforcement learning combined with vector databases optimize user interest recognition and video summarization query efficiency?

UbiComp '24ChatCam: Embracing LLMs for Contextual Chatting-to-Camera with Interest-Oriented Video Summarization

lightbulbPractical problemDecision Optimization and Reinforcement Learning Understanding

Users struggle to quickly obtain video summary content aligned with their interests using existing technologies.

UbiComp '24ChatCam: Embracing LLMs for Contextual Chatting-to-Camera with Interest-Oriented Video Summarization

helpResearch questionDecision Optimization and Reinforcement Learning Understanding

How can mechanisms from attribution theory of emotion (e.g., goal relevance, novelty, goal conduciveness, controllability) be integrated into reinforcement learning to simulate emotional change?

CHI '24Simulating Emotions With an Integrated Computational Model of Appraisal and Reinforcement Learning

helpResearch questionDecision Optimization and Reinforcement Learning Understanding

Can dynamic emotion modeling based on reinforcement learning and attribution theory accurately predict users' emotional states (e.g., 'happy,' 'bored,' 'angry')?

CHI '24Simulating Emotions With an Integrated Computational Model of Appraisal and Reinforcement Learning

helpResearch questionDecision Optimization and Reinforcement Learning Understanding

Which experimental tasks and scenarios are suitable for validating the accuracy and applicability of dynamic emotion models?

CHI '24Simulating Emotions With an Integrated Computational Model of Appraisal and Reinforcement Learning

lightbulbPractical problemDecision Optimization and Reinforcement Learning Understanding

Users' dynamic emotional changes are difficult to predict in real time and explain effectively.

CHI '24Simulating Emotions With an Integrated Computational Model of Appraisal and Reinforcement Learning

helpResearch questionDecision Optimization and Reinforcement Learning Understanding

How can reinforcement-learning-based attention management systems optimize users' task-switching performance?

CHI '24Supporting Task Switching with Reinforcement Learning

helpResearch questionDecision Optimization and Reinforcement Learning Understanding

What specific performance improvements does adding a cognitive constraint model bring in multitasking environments?

CHI '24Supporting Task Switching with Reinforcement Learning

helpResearch questionDecision Optimization and Reinforcement Learning Understanding

What advantages does a cognitive model provide over users' self-switching strategies in experimental settings?

CHI '24Supporting Task Switching with Reinforcement Learning

lightbulbPractical problemDecision Optimization and Reinforcement Learning Understanding

Users in high-stress multitasking situations easily reduce efficiency or make errors due to frequent task switching.

CHI '24Supporting Task Switching with Reinforcement Learning

helpResearch questionDecision Optimization and Reinforcement Learning Understanding

How can resource management strategies for space-air-ground integrated networks (SAGIN) be optimized to meet smart city needs?

UbiComp '23Cooperative Multi-Type Multi-Agent Deep Reinforcement Learning for Resource Management in Space-Air-Ground Integrated Networks

helpResearch questionDecision Optimization and Reinforcement Learning Understanding

How can multiple types of intelligent agents collaborate to optimize data transmission rates and reduce latency in dynamic networks?

UbiComp '23Cooperative Multi-Type Multi-Agent Deep Reinforcement Learning for Resource Management in Space-Air-Ground Integrated Networks

helpResearch questionDecision Optimization and Reinforcement Learning Understanding

Can deep reinforcement learning-based multi-agent systems improve communication and resource management efficiency in heterogeneous networks?

UbiComp '23Cooperative Multi-Type Multi-Agent Deep Reinforcement Learning for Resource Management in Space-Air-Ground Integrated Networks

lightbulbPractical problemDecision Optimization and Reinforcement Learning Understanding

Smart cities' demand for efficient communication networks cannot be met by ground networks alone.

UbiComp '23Cooperative Multi-Type Multi-Agent Deep Reinforcement Learning for Resource Management in Space-Air-Ground Integrated Networks

helpResearch questionDecision Optimization and Reinforcement Learning Understanding

How can autonomous aircraft effectively handle ground effect and control noise during landing?

UbiComp '23SmoothLander: A Quadrotor Landing Control System with Smooth Trajectory Guarantee Based on Reinforcement Learning

helpResearch questionDecision Optimization and Reinforcement Learning Understanding

Can smooth landing be achieved through reinforcement-learning pre-generated control commands?

UbiComp '23SmoothLander: A Quadrotor Landing Control System with Smooth Trajectory Guarantee Based on Reinforcement Learning

helpResearch questionDecision Optimization and Reinforcement Learning Understanding

How can a physics-driven ground effect model be built to improve autonomous aircraft landing stability?

UbiComp '23SmoothLander: A Quadrotor Landing Control System with Smooth Trajectory Guarantee Based on Reinforcement Learning

lightbulbPractical problemDecision Optimization and Reinforcement Learning Understanding

Drones are prone to instability or damage during landing due to ground effect and noise interference.

UbiComp '23SmoothLander: A Quadrotor Landing Control System with Smooth Trajectory Guarantee Based on Reinforcement Learning

helpResearch questionDecision Optimization and Reinforcement Learning Understanding

How can reinforcement learning optimize experimental design to improve efficiency of user model parameter estimation?

CHI '23Amortised Experimental Design and Parameter Estimation for User Models of Pointing

helpResearch questionDecision Optimization and Reinforcement Learning Understanding

Can rapid user model parameter estimation be achieved without relying on large-scale user data?

CHI '23Amortised Experimental Design and Parameter Estimation for User Models of Pointing

helpResearch questionDecision Optimization and Reinforcement Learning Understanding

Can non-differentiable simulators be applied to complex user behavior modeling?

CHI '23Amortised Experimental Design and Parameter Estimation for User Models of Pointing

lightbulbPractical problemDecision Optimization and Reinforcement Learning Understanding

User model parameter estimation requires large amounts of user data, making the process expensive and time-consuming.

CHI '23Amortised Experimental Design and Parameter Estimation for User Models of Pointing

helpResearch questionDecision Optimization and Reinforcement Learning Understanding

How can muscle-driven control and perception-based reinforcement learning simulate more realistic user interaction behavior?

UIST '22Breathing Life Into Biomechanical User Models

helpResearch questionDecision Optimization and Reinforcement Learning Understanding

Can user models improve simulation of complex interaction tasks through perception models (e.g., RGB-D cameras) and muscle modeling?

UIST '22Breathing Life Into Biomechanical User Models

helpResearch questionDecision Optimization and Reinforcement Learning Understanding

How does this generative biomechanical model perform in UI performance evaluation and human motion pattern prediction?

UIST '22Breathing Life Into Biomechanical User Models

lightbulbPractical problemDecision Optimization and Reinforcement Learning Understanding

Traditional user models cannot realistically simulate human interaction with physical devices or interfaces.

UIST '22Breathing Life Into Biomechanical User Models

helpResearch questionDecision Optimization and Reinforcement Learning Understanding

On small touchscreen devices, how should decisions be made about whether to provide target suggestions to improve selection accuracy?

CHI '22Select or Suggest? Reinforcement Learning-based Method for High-Accuracy Target Selection on Touchscreens

helpResearch questionDecision Optimization and Reinforcement Learning Understanding

Can reinforcement learning methods dynamically optimize when and what suggestions to provide in touchscreen target selection?

CHI '22Select or Suggest? Reinforcement Learning-based Method for High-Accuracy Target Selection on Touchscreens

helpResearch questionDecision Optimization and Reinforcement Learning Understanding

While improving selection accuracy, how can user operation time costs be balanced?

CHI '22Select or Suggest? Reinforcement Learning-based Method for High-Accuracy Target Selection on Touchscreens

lightbulbPractical problemDecision Optimization and Reinforcement Learning Understanding

Users easily make errors when selecting targets on small touchscreen devices, reducing efficiency.

CHI '22Select or Suggest? Reinforcement Learning-based Method for High-Accuracy Target Selection on Touchscreens

helpResearch questionDecision Optimization and Reinforcement Learning Understanding

How do humans learn and adapt to affordances of new objects or interfaces through interaction dynamics?

CHI '22Rediscovering Affordance: A Reinforcement Learning Perspective

helpResearch questionDecision Optimization and Reinforcement Learning Understanding

How can ecological and cognitive categorization perspectives be combined with reinforcement learning theory to explain affordance formation?

CHI '22Rediscovering Affordance: A Reinforcement Learning Perspective

helpResearch questionDecision Optimization and Reinforcement Learning Understanding

Can reinforcement learning simulate humans' adaptation to misleading interface components and adjust behavior in human-like ways?

CHI '22Rediscovering Affordance: A Reinforcement Learning Perspective

lightbulbPractical problemDecision Optimization and Reinforcement Learning Understanding

Users struggle to intuitively understand available functions when first using new interfaces or misleading designs.

CHI '22Rediscovering Affordance: A Reinforcement Learning Perspective

helpResearch questionDecision Optimization and Reinforcement Learning Understanding

How can reinforcement learning optimize order allocation strategies in public-transit-based crowdsourced delivery systems?

UbiComp '21A City-Wide Crowdsourcing Delivery System with Reinforcement Learning

helpResearch questionDecision Optimization and Reinforcement Learning Understanding

How can practical constraints such as delivery time limits, profit maximization, and passenger willingness be balanced in multi-hop route delivery?

UbiComp '21A City-Wide Crowdsourcing Delivery System with Reinforcement Learning

helpResearch questionDecision Optimization and Reinforcement Learning Understanding

Can an ETA module provide statistical support during training and accelerate reinforcement learning model convergence?

UbiComp '21A City-Wide Crowdsourcing Delivery System with Reinforcement Learning

lightbulbPractical problemDecision Optimization and Reinforcement Learning Understanding

Urban delivery demand is surging; existing methods struggle to efficiently handle time constraints and profit optimization.

UbiComp '21A City-Wide Crowdsourcing Delivery System with Reinforcement Learning

helpResearch questionDecision Optimization and Reinforcement Learning Understanding

How can reinforcement learning techniques be used to design intervention strategies that help users improve sleep habits through inverse planning?

UbiComp '21Effects of Intervening Backwards from Goals to Improve Sleep Habits

helpResearch questionDecision Optimization and Reinforcement Learning Understanding

Are inverse planning intervention strategies more effective than traditional simple reminders?

UbiComp '21Effects of Intervening Backwards from Goals to Improve Sleep Habits

helpResearch questionDecision Optimization and Reinforcement Learning Understanding

How can users more naturally achieve sleep goals through goal-related precursor activities?

UbiComp '21Effects of Intervening Backwards from Goals to Improve Sleep Habits

lightbulbPractical problemDecision Optimization and Reinforcement Learning Understanding

Existing sleep intervention tools rely on overly simplistic reminders with limited effectiveness, failing to help users truly achieve sleep goals.

UbiComp '21Effects of Intervening Backwards from Goals to Improve Sleep Habits

helpResearch questionDecision Optimization and Reinforcement Learning Understanding

How can visual perception, intermittent motor control, and click decision processes in dynamic pointing be simulated?

CHI '21A Simulation Model of Intermittently Controlled Point-and-Click Behaviour

helpResearch questionDecision Optimization and Reinforcement Learning Understanding

Can deep reinforcement learning optimize user behavior strategies for more realistic pointing behavior simulation?

CHI '21A Simulation Model of Intermittently Controlled Point-and-Click Behaviour

Adjacent categories

Human-AI Collaboration and Decision Support

Decision Optimization and Reinforcement Learning Understanding

All questions

Related papers

Simulating Emotions With an Integrated Computational Model of Appraisal and Reinforcement Learning

Supporting Task Switching with Reinforcement Learning

Amortised Experimental Design and Parameter Estimation for User Models of Pointing

Breathing Life Into Biomechanical User Models

Select or Suggest? Reinforcement Learning-based Method for High-Accuracy Target Selection on Touchscreens

Rediscovering Affordance: A Reinforcement Learning Perspective

A Simulation Model of Intermittently Controlled Point-and-Click Behaviour

Touchscreen Typing As Optimal Supervisory Control

Optimal Action-based or User Prediction-based Haptic Guidance: Can You Do Even Better?

Adapting User Interfaces with Model-based Reinforcement Learning

Adjacent categories

Human-AI Collaborative Decision-Making and Advice Adoption

Human-AI Collaborative Optimization and Preference Alignment

Embodied AI Collaboration and Intent Understanding

AI Latency Inference and Responsibility Allocation

Human-AI Co-Adaptation and Capability Augmentation

Human-AI Collaborative System Testing and Evaluation