3 citations · 7 across the 7 of their papers we have counts for
7 papers
Selective imitation on the basis of reward function similarity
Max Taylor-Davies, Stephanie Droop, Christopher G. Lucas
Imitation is a key component of human social behavior, and is widely used by both children and adults as a way to navigate uncertain or unfamiliar situations. But in an environment…
Causal Explanations for Sequential Decision-Making in Multi-Agent Systems
Balint Gyevnar, Cheng Wang, Christopher G. Lucas +2
We present CEMA: Causal Explanations in Multi-Agent systems; a framework for creating causal natural language explanations of an agent's decisions in dynamic sequential multi-agent…
A Human-Centric Method for Generating Causal Explanations in Natural Language for Autonomous Vehicle Motion Planning
Balint Gyevnar, Massimiliano Tamborski, Cheng Wang +3
Inscrutable AI systems are difficult to trust, especially if they operate in safety-critical settings like autonomous driving. Therefore, there is a need to build transparent and q…
Actively learning to learn causal relationships
Chentian Jiang, Christopher G. Lucas
How do people actively learn to learn? That is, how and when do people choose actions that facilitate long-term learning and choosing future actions that are more informative? We e…
Building Object-based Causal Programs for Human-like Generalization
Bonan Zhao, Christopher G. Lucas, Neil R. Bramley
We present a novel task that measures how people generalize objects' causal powers based on observing a single (Experiment 1) or a few (Experiment 2) causal interactions between ob…
Optimising Placement of Pollution Sensors in Windy Environments
Sigrid Passano Hellan, Christopher G. Lucas, Nigel H. Goddard
Air pollution is one of the most important causes of mortality in the world. Monitoring air pollution is useful to learn more about the link between health and pollutants, and to i…
The Human Kernel
Andrew Gordon Wilson, Christoph Dann, Christopher G. Lucas +1
Bayesian nonparametric models, such as Gaussian processes, provide a compelling framework for automatic statistical modelling: these models have a high degree of flexibility, and a…