Decoupling Strategy and Generation in Negotiation Dialogues

@article{He2018DecouplingSA,
  title={Decoupling Strategy and Generation in Negotiation Dialogues},
  author={He He and Derek Chen and Anusha Balakrishnan and Percy Liang},
  journal={ArXiv},
  year={2018},
  volume={abs/1808.09637}
}
We consider negotiation settings in which two agents use natural language to bargain on goods. [...] Key Method We show that we can flexibly set the strategy using supervised learning, reinforcement learning, or domain-specific knowledge without degeneracy, while our retrieval-based generation can maintain context-awareness and produce diverse utterances. We test our approach on the recently proposed DEALORNODEAL game, and we also collect a richer dataset based on real items on Craigslist. Human evaluation…Expand
BERT in Negotiations: Early Prediction of Buyer-Seller Negotiation Outcomes
GoChat: Goal-oriented Chatbots with Hierarchical Reinforcement Learning
Show, Price and Negotiate: A Hierarchical Attention Recurrent Visual Negotiator
Breakdown Detection in Negotiation Dialogues (Student Abstract)
Generalized Conditioned Dialogue Generation Based on Pre-trained Language Model
Targeted Data Acquisition for Evolving Negotiation Agents
Generating Strategic Dialogue for Negotiation with Theory of Mind
...
1
2
3
4
5
...

References

SHOWING 1-10 OF 33 REFERENCES
Deal or No Deal? End-to-End Learning of Negotiation Dialogues
Strategic Dialogue Management via Deep Reinforcement Learning
Deep Reinforcement Learning for Dialogue Generation
End-to-End Reinforcement Learning of Dialogue Agents for Information Access
Evaluating Persuasion Strategies and Deep Reinforcement Learning methods for Negotiation Dialogue agents
Modelling Strategic Conversation: model, annotation design and corpus
Reinforcement Learning in Multi-Party Trading Dialog
Latent Intention Dialogue Models
Training End-to-End Dialogue Systems with the Ubuntu Dialogue Corpus
Emergent Communication through Negotiation
...
1
2
3
4
...