Unifying Count-Based Exploration and Intrinsic Motivation

We consider an agent's uncertainty about its environment and the problem of generalizing this uncertainty across observations. Specifically, we focus on the problem of exploration in non-tabular reinforcement learning... (read more)

PDF Abstract NeurIPS 2016 PDF NeurIPS 2016 Abstract
TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT BENCHMARK
Atari Games Atari 2600 Freeway A3C-CTS Score 30.48 # 17
Atari Games Atari 2600 Gravitar A3C-CTS Score 238.68 # 39
Atari Games Atari 2600 Montezuma's Revenge A3C-CTS Score 273.7 # 17
Atari Games Atari 2600 Montezuma's Revenge DDQN-PC Score 3459 # 7
Atari Games Atari 2600 Private Eye A3C-CTS Score 99.32 # 35
Atari Games Atari 2600 Venture A3C-CTS Score 0.0 # 38

Methods used in the Paper


METHOD TYPE
🤖 No Methods Found Help the community by adding them if they're not listed; e.g. Deep Residual Learning for Image Recognition uses ResNet