4 papers
Reinforcing Real-world Service Agents: Balancing Utility and Cost in Task-oriented Dialogue
Ning Gao, Wei Zhang, Yuqin Dai +6
The rapid evolution of Large Language Models (LLMs) has accelerated the transition from conversational chatbots to general agents. However, effectively balancing empathetic communi…
Multi-Agent Reinforcement Learning for Market Making: Competition without Collusion
Ziyi Wang, Carmine Ventre, Maria Polukarov
Algorithmic collusion has emerged as a central question in AI: Will the interaction between different AI agents deployed in markets lead to collusion? More generally, understanding…
ARL-Based Multi-Action Market Making with Hawkes Processes and Variable Volatility
Ziyi Wang, Carmine Ventre, Maria Polukarov
We advance market-making strategies by integrating Adversarial Reinforcement Learning (ARL), Hawkes Processes, and variable volatility levels while also expanding the action space…
Robust Market Making: To Quote, or not To Quote
Ziyi Wang, Carmine Ventre, Maria Polukarov
Market making is a popular trading strategy, which aims to generate profit from the spread between the quotes posted at either side of the market. It has been shown that training m…