3 papers
ASPECT:Analogical Semantic Policy Execution via Language Conditioned Transfer
Ajsal Shereef Palattuparambil, Thommen George Karimpanal, Santu Rana
Reinforcement Learning (RL) agents often struggle to generalize knowledge to new tasks, even those structurally similar to ones they have mastered. Although recent approaches have…
MAGIK: Mapping to Analogous Goals via Imagination-enabled Knowledge Transfer
Ajsal Shereef Palattuparambil, Thommen George Karimpanal, Santu Rana
Humans excel at analogical reasoning - applying knowledge from one task to a related one with minimal relearning. In contrast, reinforcement learning (RL) agents typically require…
Dynamic Policy Fusion for User Alignment Without Re-Interaction
Ajsal Shereef Palattuparambil, Thommen George Karimpanal, Santu Rana
Deep reinforcement learning (RL) policies, although optimal in terms of task rewards, may not align with the personal preferences of human users. To ensure this alignment, a naive…