Towards Explainable Strategy Templates using NLP Transformers

no code implementations • 23 Nov 2023 • 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 language explanations.

Learnable Strategies for Bilateral Agent Negotiation over Multiple Issues

no code implementations • 17 Sep 2020 • 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.

Decision Making

A Deep Reinforcement Learning Approach to Concurrent Bilateral Negotiation

no code implementations • 31 Jan 2020 • Pallavi Bagga, Nicola Paoletti, Bedour Alrayes, Kostas Stathis

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.

reinforcement-learning Reinforcement Learning (RL)