6 papers
Redistribution-based Cost Inference Improves Sparse Safe Offline RL
Ebenezer Gelo, Geraud Nangue Tasse, Steven James +1
Safe offline RL typically assumes access to dense per-step cost annotations, but in practice supervisors provide only trajectory-level stop-feedback: a binary signal at the first u…
CORDA: A Benchmark for Hierarchical Harm-Centric Moral Reasoning in Large Language Models
Siddarth Singh, Victoria Williams, Simon Rosen +6
The key question in moral judgement is not simply whether someone chooses the "right" answer, but how they decide what matters most when moral principles conflict. Current evaluati…
Unsupervised Hierarchical Skill Discovery
Damion Harvey, Geraud Nangue Tasse, Benjamin Rosman +2
We consider the problem of unsupervised skill segmentation and hierarchical structure discovery in reinforcement learning. While recent approaches have sought to segment trajectori…
MoralityGym: A Benchmark for Evaluating Hierarchical Moral Alignment in Sequential Decision-Making Agents
Simon Rosen, Siddarth Singh, Ebenezer Gelo +6
Evaluating moral alignment in agents navigating conflicting, hierarchically structured human norms is a critical challenge at the intersection of AI safety, moral philosophy, and c…
Beyond Sliding Windows: Learning to Manage Memory in Non-Markovian Environments
Geraud Nangue Tasse, Matthew Riemer, Benjamin Rosman +1
Recent success in developing increasingly general purpose agents based on sequence models has led to increased focus on the problem of deploying computationally limited agents with…
Compositional Instruction Following with Language Models and Reinforcement Learning
Vanya Cohen, Geraud Nangue Tasse, Nakul Gopalan +4
Combining reinforcement learning with language grounding is challenging as the agent needs to explore the environment while simultaneously learning multiple language-conditioned ta…