154 citations · 162 across the 9 of their papers we have counts for
9 papers
Learning When to Cooperate Under Heterogeneous Goals
Max Taylor-Davies, Neil Bramley, Christopher G. Lucas
A significant element of human cooperative intelligence lies in our ability to identify opportunities for fruitful collaboration; and conversely to recognise when the task at hand…
Partner Modelling Emerges in Recurrent Agents (But Only When It Matters)
Ruaridh Mon-Williams, Max Taylor-Davies, Elizabeth Mieczkowski +5
Humans are remarkably adept at collaboration, able to infer the strengths and weaknesses of new partners in order to work successfully towards shared goals. To build AI systems wit…
Predicting Multi-Agent Specialization via Task Parallelizability
Elizabeth Mieczkowski, Ruaridh Mon-Williams, Neil Bramley +3
When should we encourage specialization in multi-agent systems versus train generalists that perform the entire task independently? We propose that specialization largely depends o…
People Attribute Purpose to Autonomous Vehicles When Explaining Their Behavior: Insights from Cognitive Science for Explainable AI
Balint Gyevnar, Stephanie Droop, Tadeg Quillien +4
It is often argued that effective human-centered explainable artificial intelligence (XAI) should resemble human reasoning. However, empirical investigations of how concepts from c…
Modeling infant object perception as program induction
Jan-Philipp Fränken, Christopher G. Lucas, Neil R. Bramley +1
Infants expect physical objects to be rigid and persist through space and time and in spite of occlusion. Developmentists frequently attribute these expectations to a "core system"…
Designing Optimal Behavioral Experiments Using Machine Learning
Simon Valentin, Steven Kleinegesse, Neil R. Bramley +3
Computational models are powerful tools for understanding human cognition and behavior. They let us express our theories clearly and precisely, and offer predictions that can be su…
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…
Bayesian Optimal Experimental Design for Simulator Models of Cognition
Simon Valentin, Steven Kleinegesse, Neil R. Bramley +2
Bayesian optimal experimental design (BOED) is a methodology to identify experiments that are expected to yield informative data. Recent work in cognitive science considered BOED f…
Formalizing Neurath's Ship: Approximate Algorithms for Online Causal Learning
Neil R. Bramley, Peter Dayan, Thomas L. Griffiths +1
Higher-level cognition depends on the ability to learn models of the world. We can characterize this at the computational level as a structure-learning problem with the goal of bes…