Search Results for author:
Found 10 papers, 3 papers with code
Routing and Scheduling in Answer Set Programming applied to Multi-Agent Path Finding: Preliminary Report
We present alternative approaches to routing and scheduling in Answer Set Programming (ASP), and explore them in the context of Multi-agent Path Finding.
plingo: A system for probabilistic reasoning in clingo based on lpmln
We present plingo, an extension of the ASP system clingo with various probabilistic reasoning modes.
On the Foundations of Grounding in Answer Set Programming
We provide a comprehensive elaboration of the theoretical foundations of variable instantiation, or grounding, in Answer Set Programming (ASP).
How to build your own ASP-based system?!
This is arguably due to its attractive modeling-grounding-solving workflow that provides an easy approach to problem solving, even for laypersons outside computer science.
ASP-Core-2 Input Language Format
Standardization of solver input languages has been a main driver for the growth of several areas within knowledge representation and reasoning, fostering the exploitation in actual applications.
Temporal Answer Set Programming on Finite Traces
In this paper, we introduce an alternative approach to Temporal Answer Set Programming that relies on a variation of Temporal Equilibrium Logic (TEL) for finite traces.
Clingo goes Linear Constraints over Reals and Integers
The recent series 5 of the ASP system clingo provides generic means to enhance basic Answer Set Programming (ASP) with theory reasoning capabilities.
Multi-shot ASP solving with clingo
We introduce a new flexible paradigm of grounding and solving in Answer Set Programming (ASP), which we refer to as multi-shot ASP solving, and present its implementation in the ASP system clingo.
Grounding Recursive Aggregates: Preliminary Report
In particular, we provide a series of algorithms detailing the treatment of recursive aggregates and illustrate this by a running example.
Solver Scheduling via Answer Set Programming
Although Boolean Constraint Technology has made tremendous progress over the last decade, the efficacy of state-of-the-art solvers is known to vary considerably across different types of problem instances and is known to depend strongly on algorithm parameters.
