3 citations · 9 across the 10 of their papers we have counts for
6 papers · 1 filter
Distributed Partial Information Puzzles: Examining Common Ground Construction Under Epistemic Asymmetry
Yifan Zhu, Mariah Bradford, Kenneth Lai +4
Establishing common ground, a shared set of beliefs and mutually recognized facts, is fundamental to collaboration, yet remains a challenge for current AI systems, especially in mu…
Metacognitive AI: Framework and the Case for a Neurosymbolic Approach
Hua Wei, Paulo Shakarian, Christian Lebiere +3
Metacognition is the concept of reasoning about an agent's own internal processes and was originally introduced in the field of developmental psychology. In this position paper, we…
Exploiting Embodied Simulation to Detect Novel Object Classes Through Interaction
Nikhil Krishnaswamy, Sadaf Ghaffari
In this paper we present a novel method for a naive agent to detect novel objects it encounters in an interaction. We train a reinforcement learning policy on a stacking task given…
Neurosymbolic AI for Situated Language Understanding
Nikhil Krishnaswamy, James Pustejovsky
In recent years, data-intensive AI, particularly the domain of natural language processing and understanding, has seen significant progress driven by the advent of large datasets a…
Situational Grounding within Multimodal Simulations
James Pustejovsky, Nikhil Krishnaswamy
In this paper, we argue that simulation platforms enable a novel type of embodied spatial reasoning, one facilitated by a formal model of object and event semantics that renders th…
Combining Deep Learning and Qualitative Spatial Reasoning to Learn Complex Structures from Sparse Examples with Noise
Nikhil Krishnaswamy, Scott Friedman, James Pustejovsky
Many modern machine learning approaches require vast amounts of training data to learn new concepts; conversely, human learning often requires few examples--sometimes only one--fro…