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Found 9 papers, 2 papers with code
Optimal Alignment of Temporal Knowledge Bases
Answering temporal CQs over temporalized Description Logic knowledge bases (TKB) is a main technique to realize ontology-based situation recognition.
Exploiting Multiple Abstractions in Episodic RL via Reward Shaping
One major limitation to the applicability of Reinforcement Learning (RL) to many practical domains is the large number of samples required to learn an optimal policy.
Mimicking Behaviors in Separated Domains
Devising a strategy to make a system mimicking behaviors from another system is a problem that naturally arises in many areas of Computer Science.
ASP-Based Declarative Process Mining (Extended Abstract)
We propose Answer Set Programming (ASP) as an approach for modeling and solving problems from the area of Declarative Process Mining (DPM).
Monitoring Hybrid Process Specifications with Conflict Management: The Automata-theoretic Approach
For example, in the medical domain, a clinical guideline describing the treatment of a specific disease cannot account for all possible co-factors that can coexist for a specific patient and therefore additional constraints may need to be considered.
Foundations for Restraining Bolts: Reinforcement Learning with LTLf/LDLf restraining specifications
In this work we investigate on the concept of "restraining bolt", envisioned in Science Fiction.
Situation Calculus for Synthesis of Manufacturing Controllers
Manufacturing is transitioning from a mass production model to a manufacturing as a service model in which manufacturing facilities 'bid' to produce products.
Specifying Non-Markovian Rewards in MDPs Using LDL on Finite Traces (Preliminary Version)
In Markov Decision Processes (MDPs), the reward obtained in a state depends on the properties of the last state and action.
Bounded Situation Calculus Action Theories
A bounded action theory is one which entails that, in every situation, the number of object tuples in the extension of fluents is bounded by a given constant, although such extensions are in general different across the infinitely many situations.
