7 citations · 12 across the 8 of their papers we have counts for
10 papers
MinMax Recurrent Neural Cascades
Alessandro Ronca
We introduce MinMax Recurrent Neural Cascades (MinMax RNCs), a class of recurrent neural networks built from a novel form of recurrence over the MinMax algebra. We show that MinMax…
Tractable Offline Learning of Regular Decision Processes
Ahana Deb, Roberto Cipollone, Anders Jonsson +2
This work studies offline Reinforcement Learning (RL) in a class of non-Markovian environments called Regular Decision Processes (RDPs). In RDPs, the unknown dependency of future o…
On the Expressivity of Recurrent Neural Cascades with Identity
Nadezda Alexandrovna Knorozova, Alessandro Ronca
Recurrent Neural Cascades (RNC) are the class of recurrent neural networks with no cyclic dependencies among recurrent neurons. Their subclass RNC+ with positive recurrent weights…
On The Expressivity of Recurrent Neural Cascades
Nadezda Alexandrovna Knorozova, Alessandro Ronca
Recurrent Neural Cascades (RNCs) are the recurrent neural networks with no cyclic dependencies among recurrent neurons. This class of recurrent networks has received a lot of atten…
The Transformation Logics
Alessandro Ronca
We introduce a new family of temporal logics designed to finely balance the trade-off between expressivity and complexity. Their key feature is the possibility of defining operator…
Automata Cascades: Expressivity and Sample Complexity
Alessandro Ronca, Nadezda Alexandrovna Knorozova, Giuseppe De Giacomo
Every automaton can be decomposed into a cascade of basic prime automata. This is the Prime Decomposition Theorem by Krohn and Rhodes. Guided by this theory, we propose automata ca…
Markov Abstractions for PAC Reinforcement Learning in Non-Markov Decision Processes
Alessandro Ronca, Gabriel Paludo Licks, Giuseppe De Giacomo
Our work aims at developing reinforcement learning algorithms that do not rely on the Markov assumption. We consider the class of Non-Markov Decision Processes where histories can…
Efficient PAC Reinforcement Learning in Regular Decision Processes
Alessandro Ronca, Giuseppe De Giacomo
Recently regular decision processes have been proposed as a well-behaved form of non-Markov decision process. Regular decision processes are characterised by a transition function…
The Window Validity Problem in Rule-Based Stream Reasoning
Alessandro Ronca, Mark Kaminski, Bernardo Cuenca Grau +1
Rule-based temporal query languages provide the expressive power and flexibility required to capture in a natural way complex analysis tasks over streaming data. Stream processing…
Stream Reasoning in Temporal Datalog
Alessandro Ronca, Mark Kaminski, Bernardo Cuenca Grau +2
In recent years, there has been an increasing interest in extending traditional stream processing engines with logical, rule-based, reasoning capabilities. This poses significant t…