8 citations · 8 across the 2 of their papers we have counts for
7 papers
Planning for Proactive Assistance in Environments with Partial Observability
Anagha Kulkarni, Siddharth Srivastava, Subbarao Kambhampati
This paper addresses the problem of synthesizing the behavior of an AI agent that provides proactive task assistance to a human in settings like factory floors where they may coexi…
A Unifying Bayesian Formulation of Measures of Interpretability in Human-AI
Sarath Sreedharan, Anagha Kulkarni, David E. Smith +1
Existing approaches for generating human-aware agent behaviors have considered different measures of interpretability in isolation. Further, these measures have been studied under…
A Bayesian Account of Measures of Interpretability in Human-AI Interaction
Sarath Sreedharan, Anagha Kulkarni, Tathagata Chakraborti +2
Existing approaches for the design of interpretable agent behavior consider different measures of interpretability in isolation. In this paper we posit that, in the design and depl…
Designing Environments Conducive to Interpretable Robot Behavior
Anagha Kulkarni, Sarath Sreedharan, Sarah Keren +3
Designing robots capable of generating interpretable behavior is a prerequisite for achieving effective human-robot collaboration. This means that the robots need to be capable of…
Signaling Friends and Head-Faking Enemies Simultaneously: Balancing Goal Obfuscation and Goal Legibility
Anagha Kulkarni, Siddharth Srivastava, Subbarao Kambhampati
In order to be useful in the real world, AI agents need to plan and act in the presence of others, who may include adversarial and cooperative entities. In this paper, we consider…
Explicability? Legibility? Predictability? Transparency? Privacy? Security? The Emerging Landscape of Interpretable Agent Behavior
Tathagata Chakraborti, Anagha Kulkarni, Sarath Sreedharan +2
There has been significant interest of late in generating behavior of agents that is interpretable to the human (observer) in the loop. However, the work in this area has typically…