1 citations · 2 across the 10 of their papers we have counts for
5 papers · 1 filter
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…
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…