3 citations · 8 across the 4 of their papers we have counts for
4 papers
Towards Explainable Strategy Templates using NLP Transformers
Pallavi Bagga, Kostas Stathis
This paper bridges the gap between mathematical heuristic strategies learned from Deep Reinforcement Learning (DRL) in automated agent negotiation, and comprehensible, natural lang…
Deep Learnable Strategy Templates for Multi-Issue Bilateral Negotiation
Pallavi Bagga, Nicola Paoletti, Kostas Stathis
We study how to exploit the notion of strategy templates to learn strategies for multi-issue bilateral negotiation. Each strategy template consists of a set of interpretable parame…
Learnable Strategies for Bilateral Agent Negotiation over Multiple Issues
Pallavi Bagga, Nicola Paoletti, Kostas Stathis
We present a novel bilateral negotiation model that allows a self-interested agent to learn how to negotiate over multiple issues in the presence of user preference uncertainty. Th…
A Deep Reinforcement Learning Approach to Concurrent Bilateral Negotiation
Pallavi Bagga, Nicola Paoletti, Bedour Alrayes +1
We present a novel negotiation model that allows an agent to learn how to negotiate during concurrent bilateral negotiations in unknown and dynamic e-markets. The agent uses an act…