1 citations · 4 across the 12 of their papers we have counts for
13 papers
Companion AI and Ethical Design: Learning from System Failures and User Desires
Alicia Vidler, Belinda Middleweek
Human users are interacting with chatbots and companion AI technologies as if they were human. A growing array of AI-systems are now trained to recognise, interpret, and simulate f…
A Harmonic Mean Formulation of Average Reward Reinforcement Learning in SMDPs
Erel Shtossel, Alicia Vidler, Uri Shaham +1
Recent research has revived and amplified interest in algorithms for undiscounted average reward reinforcement learning in infinite-horizon, non-episodic (continuing) tasks. Semi-M…
Multiagent Reinforcement Learning for Liquidity Games
Alicia Vidler, Gal A. Kaminka
Making use of swarm methods in financial market modeling of liquidity, and techniques from financial analysis in swarm analysis, holds the potential to advance both research areas.…
Playing games with Large language models: Randomness and strategy
Alicia Vidler, Toby Walsh
Playing games has a long history of describing intricate interactions in simplified forms. In this paper we explore if large language models (LLMs) can play games, investigating th…
Shifting Power: Leveraging LLMs to Simulate Human Aversion in ABMs of Bilateral Financial Exchanges, A bond market study
Alicia Vidler, Toby Walsh
Bilateral markets, such as those for government bonds, involve decentralized and opaque transactions between market makers (MMs) and clients, posing significant challenges for trad…
Evaluating Binary Decision Biases in Large Language Models: Implications for Fair Agent-Based Financial Simulations
Alicia Vidler, Toby Walsh
Large Language Models (LLMs) are increasingly being used to simulate human-like decision making in agent-based financial market models (ABMs). As models become more powerful and ac…
Decoding OTC Government Bond Market Liquidity: An ABM Model for Market Dynamics
Alicia Vidler, Toby Walsh
The over-the-counter (OTC) government bond markets are characterised by their bilateral trading structures, which pose unique challenges to understanding and ensuring market stabil…
TraderTalk: An LLM Behavioural ABM applied to Simulating Human Bilateral Trading Interactions
Alicia Vidler, Toby Walsh
We introduce a novel hybrid approach that augments Agent-Based Models (ABMs) with behaviors generated by Large Language Models (LLMs) to simulate human trading interactions. We cal…
The role of gender in promotion rates in the Australian Finance Industry
Cassandra Crowe, Belinda Middleweek, Laura Ryan +2
We surveyed Australian finance professionals and tested whether there are statistically significant differences in promotional propensity according to gender identity. The findings…
Non cooperative Liquidity Games and their application to bond market trading
Alicia Vidler, Toby Walsh
We present a new type of game, the Liquidity Game. We draw inspiration from the UK government bond market and apply game theoretic approaches to its analysis. In Liquidity Games, m…
Modelling Opaque Bilateral Market Dynamics in Financial Trading: Insights from a Multi-Agent Simulation Study
Alicia Vidler, Toby Walsh
Exploring complex adaptive financial trading environments through multi-agent based simulation methods presents an innovative approach within the realm of quantitative finance. Des…
Recommender Systems in Financial Trading: Using machine-based conviction analysis in an explainable AI investment framework
Alicia Vidler
Traditionally, assets are selected for inclusion in a portfolio (long or short) by human analysts. Teams of human portfolio managers (PMs) seek to weigh and balance these securitie…
What Type of Explanation Do Rejected Job Applicants Want? Implications for Explainable AI
Matthew Olckers, Alicia Vidler, Toby Walsh
Rejected job applicants seldom receive explanations from employers. Techniques from Explainable AI (XAI) could provide explanations at scale. Although XAI researchers have develope…