4 papers
POrTAL: Plan-Orchestrated Tree Assembly for Lookahead
Evan Conway, David Porfirio, David Chan +2
When tasking robots in partially observable environments, these robots must efficiently and robustly plan to achieve task goals under uncertainty. Although many probabilistic plann…
Procedural Knowledge Improves Agentic LLM Workflows
Vincent Hsiao, Mark Roberts, Leslie Smith
Large language models (LLMs) often struggle when performing agentic tasks without substantial tool support, prom-pt engineering, or fine tuning. Despite research showing that domai…
Uncertainty Expression for Human-Robot Task Communication
David Porfirio, Mark Roberts, Laura M. Hiatt
An underlying assumption of many existing approaches to human-robot task communication is that the robot possesses a sufficient amount of environmental domain knowledge, including…
Automating Curriculum Learning for Reinforcement Learning using a Skill-Based Bayesian Network
Vincent Hsiao, Mark Roberts, Laura M. Hiatt +2
A major challenge for reinforcement learning is automatically generating curricula to reduce training time or improve performance in some target task. We introduce SEBNs (Skill-Env…