Name
Title | ||
|---|---|---|
Social signal and user adaptation in reinforcement learning-based dialogue management |
Abstract | ||
|---|---|---|
This paper investigates the conditions under which cues from social signals can be used for user adaptation (or user tracking) of a learning agent. In this work we consider the case of the Reinforcement Learning (RL) of a dialogue management module. Social signals (gazes, postures, emotions, etc.) have an undeniable importance in human interactions and can be used as an additional and user-dependent (subjective) reinforcement signal during learning. In this paper, the Kalman Temporal Differences (KTD) framework is employed in combination with a potential-based shaping reward method to properly integrate the social information in the optimisation procedure and adapt the policy to user profiles. In a second step the ability of the method to track a new user profile (after self learning of the user or switch to a new user) is shown. Experiments carried out using a state-of-the-art goal-oriented dialogue management framework with simulations support our claims. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1145/2493525.2493535 | MLIS@IJCAI |
Keywords | Field | DocType |
reward method,social information,new user profile,reinforcement learning-based dialogue management,state-of-the-art goal-oriented dialogue management,user adaptation,user profile,social signal,dialogue management module,new user,user tracking,reinforcement learning | Dialogue management,Learning agent,User profile,Computer science,Kalman filter,User modeling,Artificial intelligence,Social information,Reinforcement,Machine learning,Reinforcement learning | Conference |
Citations | PageRank | References |
7 | 0.51 | 21 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Emmanuel Ferreira | 1 | 37 | 4.23 |
| Fabrice Lefèvre | 2 | 185 | 26.62 |