Publications (10)
Reductive MDPs: A Perspective Beyond Temporal Horizons
Thomas Spooner, Rui Silva, Joshua Lockhart +2
Solving general Markov decision processes (MDPs) is a computationally hard problem. Solving finite-horizon MDPs, on the other hand, is highly tractable with well known polynomial-t…
Factored Policy Gradients: Leveraging Structure for Efficient Learning in MOMDPs
Thomas Spooner, Nelson Vadori, Sumitra Ganesh
Policy gradient methods can solve complex tasks but often fail when the dimensionality of the action-space or objective multiplicity grow very large. This occurs, in part, because…
Robust Market Making via Adversarial Reinforcement Learning
Thomas Spooner, Rahul Savani
We show that adversarial reinforcement learning (ARL) can be used to produce market marking agents that are robust to adversarial and adaptively-chosen market conditions. To apply…
Towards Multi-Agent Reinforcement Learning driven Over-The-Counter Market Simulations
Nelson Vadori, Leo Ardon, Sumitra Ganesh +7
We study a game between liquidity provider and liquidity taker agents interacting in an over-the-counter market, for which the typical example is foreign exchange. We show how a su…
Graph Reasoning with Context-Aware Linearization for Interpretable Fact Extraction and Verification
Neema Kotonya, Thomas Spooner, Daniele Magazzeni +1
This paper presents an end-to-end system for fact extraction and verification using textual and tabular evidence, the performance of which we demonstrate on the FEVEROUS dataset. W…
Towards a fully RL-based Market Simulator
Leo Ardon, Nelson Vadori, Thomas Spooner +3
We present a new financial framework where two families of RL-based agents representing the Liquidity Providers and Liquidity Takers learn simultaneously to satisfy their objective…