3 citations · 4 across the 6 of their papers we have counts for
6 papers
Robust Counterfactual Policy Optimisation via Nondeterministic Causal Models
Jessica Lally, Milad Kazemi, Nicola Paoletti +2
Counterfactual inference approaches for sequential decision-making typically assume deterministic causal models, where all randomness stems from latent variables. However, Markov D…
Causal Counterfactuals Reconsidered
Sander Beckers
I develop a novel semantics for probabilities of counterfactuals that generalizes the standard Pearlian semantics: it applies to probabilistic causal models that cannot be extended…
Large Language Models as Nondeterministic Causal Models
Sander Beckers
Recent work by Chatzi et al. and Ravfogel et al. has developed, for the first time, a method for generating counterfactuals of probabilistic Large Language Models. Such counterfact…
Actual Causation and Nondeterministic Causal Models
Sander Beckers
In (Beckers, 2025) I introduced nondeterministic causal models as a generalization of Pearl's standard deterministic causal models. I here take advantage of the increased expressiv…
Nondeterministic Causal Models
Sander Beckers
I generalize acyclic deterministic structural causal models to the nondeterministic case and argue that this offers an improved semantics for counterfactuals. The standard, determi…
Moral Responsibility for AI Systems
Sander Beckers
As more and more decisions that have a significant ethical dimension are being outsourced to AI systems, it is important to have a definition of moral responsibility that can be ap…