activity
20182022
most citedEvent-Driven Visual-Tactile Sensing and Learning for Robots

6 citations · 37 across the 15 of their papers we have counts for

collaborators

22 papers

cs.LG2022

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.…

cs.LG2022

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…

cs.LG20222 cited

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…

cs.AI2022

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…

cs.MA20225 cited

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…

cs.LG20214 cited

Deep Explicit Duration Switching Models for Time Series

Abdul Fatir Ansari, Konstantinos Benidis, Richard Kurle +5

Many complex time series can be effectively subdivided into distinct regimes that exhibit persistent dynamics. Discovering the switching behavior and the statistical patterns in th…