Imitation and Reinforcement Learning in Agents with Heterogeneous Actions

By Bob Price, Craig Boutilier. 2001

37 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Control and Systems Engineering

How researchers see this paper

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

In Artificial Intelligence

1. Sriraam Natarajan
2. Kristian Kersting
3. Ronald E. Parr
4. Kaushik Roy
5. Srijita Das
6. Darrin C. Bentivegna
7. Christopher G. Atkeson
8. Jan Peters

In Control and Systems Engineering

1. Ronald E. Parr
2. Sriraam Natarajan
3. Kristian Kersting
4. Kaushik Roy
5. Darrin C. Bentivegna
6. Christopher G. Atkeson
7. Srijita Das
8. Jan Peters

Citations in the corpus

• Fitted Q-Learning for Relational Domains (2020, background): “Consequently, a class of RL meth-ods, called Relational Markov Decision Process (RMDPs), have been developed for learning optimal behaviour in these worlds, and methods that directly learn and reason at the first-order level have been developed in the broad area of Relational Reinforcement Learning (”
• Learning from observation using primitives (2001, background): “In similar research being conducted by Price and Boutilier [102, 101], the robots are mobile robots given the task of moving to a goal location.”