79 citations · 218 across the 30 of their papers we have counts for
5 papers · 1 filter
Safety-Constrained Policy Transfer with Successor Features
Zeyu Feng, Bowen Zhang, Jianxin Bi +1
In this work, we focus on the problem of safe policy transfer in reinforcement learning: we seek to leverage existing policies when learning a new task with specified constraints.…
Observed Adversaries in Deep Reinforcement Learning
Eugene Lim, Harold Soh
In this work, we point out the problem of observed adversaries for deep policies. Specifically, recent work has shown that deep reinforcement learning is susceptible to adversarial…
SCALES: From Fairness Principles to Constrained Decision-Making
Sreejith Balakrishnan, Jianxin Bi, Harold Soh
This paper proposes SCALES, a general framework that translates well-established fairness principles into a common representation based on the Constraint Markov Decision Process (C…
MIRROR: Differentiable Deep Social Projection for Assistive Human-Robot Communication
Kaiqi Chen, Jeffrey Fong, Harold Soh
Communication is a hallmark of intelligence. In this work, we present MIRROR, an approach to (i) quickly learn human models from human demonstrations, and (ii) use the models for s…
The Dynamics of Q-learning in Population Games: a Physics-Inspired Continuity Equation Model
Shuyue Hu, Chin-Wing Leung, Ho-fung Leung +1
Although learning has found wide application in multi-agent systems, its effects on the temporal evolution of a system are far from understood. This paper focuses on the dynamics o…