154 citations · 1.1k across the 66 of their papers we have counts for
6 papers · 2 filters
Challenges of Human-Aware AI Systems
Subbarao Kambhampati
From its inception, AI has had a rather ambivalent relationship to humans---swinging between their augmentation and replacement. Now, as AI technologies enter our everyday lives at…
Learning Action Models from Disordered and Noisy Plan Traces
Hankz Hankui Zhuo, Jing Peng, Subbarao Kambhampati
There is increasing awareness in the planning community that the burden of specifying complete domain models is too high, which impedes the applicability of planning technology in…
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…
Why Couldn't You do that? Explaining Unsolvability of Classical Planning Problems in the Presence of Plan Advice
Sarath Sreedharan, Siddharth Srivastava, David Smith +1
Explainable planning is widely accepted as a prerequisite for autonomous agents to successfully work with humans. While there has been a lot of research on generating explanations…
Model-Free Model Reconciliation
Sarath Sreedharan, Alberto Olmo, Aditya Prasad Mishra +1
Designing agents capable of explaining complex sequential decisions remain a significant open problem in automated decision-making. Recently, there has been a lot of interest in de…
Expectation-Aware Planning: A Unifying Framework for Synthesizing and Executing Self-Explaining Plans for Human-Aware Planning
Sarath Sreedharan, Tathagata Chakraborti, Christian Muise +1
In this work, we present a new planning formalism called Expectation-Aware planning for decision making with humans in the loop where the human's expectations about an agent may di…