17 citations · 22 across the 6 of their papers we have counts for
6 papers
EPO: Hierarchical LLM Agents with Environment Preference Optimization
Qi Zhao, Haotian Fu, Chen Sun +1
Long-horizon decision-making tasks present significant challenges for LLM-based agents due to the need for extensive planning over multiple steps. In this paper, we propose a hiera…
Learning Abstract World Model for Value-preserving Planning with Options
Rafael Rodriguez-Sanchez, George Konidaris
General-purpose agents require fine-grained controls and rich sensory inputs to perform a wide range of tasks. However, this complexity often leads to intractable decision-making.…
Improved Inference of Human Intent by Combining Plan Recognition and Language Feedback
Ifrah Idrees, Tian Yun, Naveen Sharma +4
Conversational assistive robots can aid people, especially those with cognitive impairments, to accomplish various tasks such as cooking meals, performing exercises, or operating m…
Flipping Coins to Estimate Pseudocounts for Exploration in Reinforcement Learning
Sam Lobel, Akhil Bagaria, George Konidaris
We propose a new method for count-based exploration in high-dimensional state spaces. Unlike previous work which relies on density models, we show that counts can be derived by ave…
A Domain-Agnostic Approach for Characterization of Lifelong Learning Systems
Megan M. Baker, Alexander New, Mario Aguilar-Simon +44
Despite the advancement of machine learning techniques in recent years, state-of-the-art systems lack robustness to "real world" events, where the input distributions and tasks enc…
Transfer Learning Across Patient Variations with Hidden Parameter Markov Decision Processes
Taylor Killian, George Konidaris, Finale Doshi-Velez
Due to physiological variation, patients diagnosed with the same condition may exhibit divergent, but related, responses to the same treatments. Hidden Parameter Markov Decision Pr…