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cs.AI2025
Pushdown Reward Machines for Reinforcement Learning
Giovanni Varricchione, Toryn Q. Klassen, Natasha Alechina +3
Reward machines (RMs) are automata structures that encode (non-Markovian) reward functions for reinforcement learning (RL). RMs can reward any behaviour representable in regular la…
cs.AI2025
Probabilistic Strategy Logic with Degrees of Observability
Chunyan Mu, Nima Motamed, Natasha Alechina +1
There has been considerable work on reasoning about the strategic ability of agents under imperfect information. However, existing logics such as Probabilistic Strategy Logic are u…
cs.AI2025
Temporal Causal Reasoning with (Non-Recursive) Structural Equation Models
Maksim Gladyshev, Natasha Alechina, Mehdi Dastani +2
Structural Equation Models (SEM) are the standard approach to representing causal dependencies between variables in causal models. In this paper we propose a new interpretation of…