Agent Morality via Counterfactuals in Logic Programming

This paper presents a computational model, via Logic Programming (LP), of counterfactual reasoning with applications to agent morality. Counterfactuals are conjectures about what would have happened, had an alternative event occurred. In the first part, we show how counterfactual reasoning, inspired by Pearl’s structural causal model of counterfactuals, is modeled using LP, by benefiting from LP abduction and updating. In the second part, counterfactuals are applied to agent morality, resorting to this LP-based approach. We demonstrate its potential for specifying and querying moral issues, by examining viewpoints on moral permissibility via classic moral principles and examples taken from the literature. Finally, we discuss some potential extensions of our LP approach to cover other aspects of counterfactual reasoning and show how these aspects are relevant in modeling agent morality.