Answer Set Programming (ASP) is a declarative problem solving approach, initially tailored
to modeling problems in the area of Knowledge Representation and Reasoning (KRR) …

Abstract Multi-Agent Pathfinding (MAPF) is the problem of finding paths for multiple agents
such that each agent reaches its goal and the agents do not collide. In recent years, variants …

The SAT Competitions constitute a well-established series of yearly open international
algorithm implementation competitions, focusing on the Boolean satisfiability (or …

Answer Set Planning refers to the use of Answer Set Programming (ASP) to compute plans,
that is, solutions to planning problems, that transform a given state of the world to another …

Reduction to SAT is a very successful approach to solving hard combinatorial problems in
Artificial Intelligence and computer science in general. Most commonly, problem instances …

LTL synthesis is the task of generating a strategy that satisfies a Linear Temporal Logic
(LTL) specification interpreted over infinite traces. In this paper we examine the problem of …

Boolean satisfiability (SAT) solvers have been the subject of remarkable improvements
since the mid 90s. One of the main reasons for these improvements has been the wide …

Planning in hybrid systems is important for dealing with real-world applications. PDDL+
supports this representation of domains with mixed discrete and continuous dynamics, and …

The scalability of SAT to very large problems has been achieved in the last ten years, due to
substantially improved encodings, SAT solvers, and algorithms for scheduling the runs of …

Both search-based and translation-based planning systems usually operate on grounded
representations of the problem. Planning models, however, are commonly defined using …