9 citations · 34 across the 8 of their papers we have counts for
8 papers
Optimizing Risk-averse Human-AI Hybrid Teams
Andrew Fuchs, Andrea Passarella, Marco Conti
We anticipate increased instances of humans and AI systems working together in what we refer to as a hybrid team. The increase in collaboration is expected as AI systems gain profi…
Optimizing Delegation in Collaborative Human-AI Hybrid Teams
Andrew Fuchs, Andrea Passarella, Marco Conti
When humans and autonomous systems operate together as what we refer to as a hybrid team, we of course wish to ensure the team operates successfully and effectively. We refer to te…
Optimizing delegation between human and AI collaborative agents
Andrew Fuchs, Andrea Passarella, Marco Conti
In the context of humans operating with artificial or autonomous agents in a hybrid team, it is essential to accurately identify when to authorize those team members to perform act…
Compensating for Sensing Failures via Delegation in Human-AI Hybrid Systems
Andrew Fuchs, Andrea Passarella, Marco Conti
Given an increasing prevalence of intelligent systems capable of autonomous actions or augmenting human activities, it is important to consider scenarios in which the human, autono…
Modeling Human Behavior Part I -- Learning and Belief Approaches
Andrew Fuchs, Andrea Passarella, Marco Conti
There is a clear desire to model and comprehend human behavior. Trends in research covering this topic show a clear assumption that many view human reasoning as the presupposed sta…
Modeling Human Behavior Part II -- Cognitive approaches and Uncertainty
Andrew Fuchs, Andrea Passarella, Marco Conti
As we discussed in Part I of this topic, there is a clear desire to model and comprehend human behavior. Given the popular presupposition of human reasoning as the standard for lea…
A Cognitive Framework for Delegation Between Error-Prone AI and Human Agents
Andrew Fuchs, Andrea Passarella, Marco Conti
With humans interacting with AI-based systems at an increasing rate, it is necessary to ensure the artificial systems are acting in a manner which reflects understanding of the hum…
Theory of Mind for Deep Reinforcement Learning in Hanabi
Andrew Fuchs, Michael Walton, Theresa Chadwick +1
The partially observable card game Hanabi has recently been proposed as a new AI challenge problem due to its dependence on implicit communication conventions and apparent necessit…