1 citations · 2 across the 10 of their papers we have counts for
10 papers
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…
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…
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,…
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…
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…
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…
A multi-objective combinatorial optimisation framework for large scale hierarchical population synthesis
Imran Mahmood, Nicholas Bishop, Anisoara Calinescu +2
In agent-based simulations, synthetic populations of agents are commonly used to represent the structure, behaviour, and interactions of individuals. However, generating a syntheti…
Private Agent-Based Modeling
Ayush Chopra, Arnau Quera-Bofarull, Nurullah Giray-Kuru +2
The practical utility of agent-based models in decision-making relies on their capacity to accurately replicate populations while seamlessly integrating real-world data streams. Ye…
Causally Abstracted Multi-armed Bandits
Fabio Massimo Zennaro, Nicholas Bishop, Joel Dyer +4
Multi-armed bandits (MAB) and causal MABs (CMAB) are established frameworks for decision-making problems. The majority of prior work typically studies and solves individual MAB and…
Interventionally Consistent Surrogates for Agent-based Simulators
Joel Dyer, Nicholas Bishop, Yorgos Felekis +4
Agent-based simulators provide granular representations of complex intelligent systems by directly modelling the interactions of the system's constituent agents. Their high-fidelit…