collaborators

6 papers

cs.LG2026

Neural Network-Based Parameter Estimation of a Labour Market Agent-Based Model

M Lopes Alves, Joel Dyer, Doyne Farmer +2

Agent-based modelling (ABM) is a widespread approach to simulate complex systems. Advancements in computational processing and storage have facilitated the adoption of ABMs across…

cs.MA2025

Automatic Differentiation of Agent-Based Models

Arnau Quera-Bofarull, Nicholas Bishop, Joel Dyer +4

Agent-based models (ABMs) simulate complex systems by capturing the bottom-up interactions of individual agents comprising the system. Many complex systems of interest, such as epi…

cs.LG2025

Bayesian Decision Making around Experts

Daniel Jarne Ornia, Joel Dyer, Nicholas Bishop +2

Complex learning agents are increasingly deployed alongside existing experts, such as human operators or previously trained agents. However, it remains unclear how should learners…

cs.LG2025

Sandbagging in a Simple Survival Bandit Problem

Joel Dyer, Daniel Jarne Ornia, Nicholas Bishop +2

Evaluating the safety of frontier AI systems is an increasingly important concern, helping to measure the capabilities of such models and identify risks before deployment. However,…

cs.AI2025

Emergent Risk Awareness in Rational Agents under Resource Constraints

Daniel Jarne Ornia, Nicholas Bishop, Joel Dyer +4

Advanced reasoning models with agentic capabilities (AI agents) are deployed to interact with humans and to solve sequential decision-making problems under (approximate) utility fu…

cs.LG2025

Using causal abstractions to accelerate decision-making in complex bandit problems

Joel Dyer, Nicholas Bishop, Anisoara Calinescu +2

Although real-world decision-making problems can often be encoded as causal multi-armed bandits (CMABs) at different levels of abstraction, a general methodology exploiting the inf…