231 citations · 828 across the 31 of their papers we have counts for
Showing 2024 · cs.AIShow all
3 papers · 2 filters
cs.AI2024
Toward Universal and Interpretable World Models for Open-ended Learning Agents
Lancelot Da Costa
We introduce a generic, compositional and interpretable class of generative world models that supports open-ended learning agents. This is a sparse class of Bayesian networks capab…
cs.AI2024
Possible Principles for Aligned Structure Learning Agents
Lancelot Da Costa, Tomáš Gavenčiak, David Hyland +5
This paper offers a roadmap for the development of scalable aligned artificial intelligence (AI) from first principle descriptions of natural intelligence. In brief, a possible pat…
cs.AI2024★ 2 cited
Active Inference as a Model of Agency
Lancelot Da Costa, Samuel Tenka, Dominic Zhao +1
Is there a canonical way to think of agency beyond reward maximisation? In this paper, we show that any type of behaviour complying with physically sound assumptions about how macr…