Efficient Model-Based Exploration

By Rolf Pfeifer, B. Blumberg, Jean-Arcady Meyer, Stewart W. Wilson. 1998

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Joelle Pineau
2. Iulian Serban
3. Jianfeng Gao
4. Yoshua Bengio
5. Sergey Levine
6. Mohit Bansal
7. Lihong Li
8. Kyunghyun Cho

Citations in the corpus

• Sample Complexity Bounds of Exploration (2012, methodology): “Advanced techniques exist that guide exploration using interval estimation (Kaelbling, 1993; Meuleau and Bourgine, 1999; Wiering and Schmidhuber, 1998), information gain (Dearden et al, 1999), MDP characteristics (Ratitch and Precup, 2002), or expert demonstration (Abbeel and Ng, 2005), to name a…”
• The Bottleneck Simulator: A Model-based Deep Reinforcement Learning Approach (2018, methodology): “…: Model-based RL research dates back to the 90s, and includes well-known algorithms such as Dyna, R-max and E 3 (Sutton, 1990; Moore & Atkeson, 1993; Peng & Williams, 1993; Kuvayev & Sutton, 1997; Brafman & Tennenholtz, 2002; Kearns & Singh, 2002; Wiering & Schmidhuber, 1998; Wiering et al., 1999).”
• Learning and adaptivity in interactive recommender systems (2007, methodology): “However, the success of an optimal policy depends heavily on exploration while gaining experience [20].”