354 citations · 740 across the 11 of their papers we have counts for
10 papers · 1 filter
Zero-Shot Task Generalization with Multi-Task Deep Reinforcement Learning
Junhyuk Oh, Satinder Singh, Honglak Lee +1
As a step towards developing zero-shot task generalization capabilities in reinforcement learning (RL), we introduce a new RL problem where the agent should learn to execute sequen…
Repeated Inverse Reinforcement Learning
Kareem Amin, Nan Jiang, Satinder Singh
We introduce a novel repeated Inverse Reinforcement Learning problem: the agent has to act on behalf of a human in a sequence of tasks and wishes to minimize the number of tasks th…
Minimizing Maximum Regret in Commitment Constrained Sequential Decision Making
Qi Zhang, Satinder Singh, Edmund Durfee
In cooperative multiagent planning, it can often be beneficial for an agent to make commitments about aspects of its behavior to others, allowing them in turn to plan their own beh…
Control of Memory, Active Perception, and Action in Minecraft
Junhyuk Oh, Valliappa Chockalingam, Satinder Singh +1
In this paper, we introduce a new set of reinforcement learning (RL) tasks in Minecraft (a flexible 3D world). We then use these tasks to systematically compare and contrast existi…
Deep Learning for Reward Design to Improve Monte Carlo Tree Search in ATARI Games
Xiaoxiao Guo, Satinder Singh, Richard Lewis +1
Monte Carlo Tree Search (MCTS) methods have proven powerful in planning for sequential decision-making problems such as Go and video games, but their performance can be poor when t…
Approximate Planning for Factored POMDPs using Belief State Simplification
David A. McAllester, Satinder Singh
We are interested in the problem of planning for factored POMDPs. Building on the recent results of Kearns, Mansour and Ng, we provide a planning algorithm for factored POMDPs that…