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cs.AI2025
FORM: Learning Expressive and Transferable First-Order Logic Reward Machines
Leo Ardon, Daniel Furelos-Blanco, Roko Parac +1
Reward machines (RMs) are an effective approach for addressing non-Markovian rewards in reinforcement learning (RL) through finite-state machines. Traditional RMs, which label edge…
cs.AI2020
Induction and Exploitation of Subgoal Automata for Reinforcement Learning
Daniel Furelos-Blanco, Mark Law, Anders Jonsson +2
In this paper we present ISA, an approach for learning and exploiting subgoals in episodic reinforcement learning (RL) tasks. ISA interleaves reinforcement learning with the induct…
cs.AI2019
Solving Multiagent Planning Problems with Concurrent Conditional Effects
Daniel Furelos-Blanco, Anders Jonsson
In this work we present a novel approach to solving concurrent multiagent planning problems in which several agents act in parallel. Our approach relies on a compilation from concu…