We study best-effort strategies (aka plans) in fully observable
nondeter...
In this paper, we study LTLf synthesis under environment specifications ...
We consider an agent acting to fulfil tasks in a nondeterministic
enviro...
Goal Recognition is the task of discerning the correct intended goal tha...
We develop a general framework for abstracting the behavior of an agent ...
One major limitation to the applicability of Reinforcement Learning (RL)...
Most of the synthesis literature has focused on studying how to synthesi...
Every automaton can be decomposed into a cascade of basic automata. This...
Devising a strategy to make a system mimicking behaviors from another sy...
Our work aims at developing reinforcement learning algorithms that do no...
We study temporally extended goals expressed in Pure-Past LTL (PPLTL). P...
Fully Observable Non-Deterministic (FOND) planning models uncertainty th...
Augmented Business Process Management Systems (ABPMSs) are an emerging c...
Recently regular decision processes have been proposed as a well-behaved...
Goal Recognition is the task of discerning the correct intended goal tha...
In this paper we introduce Behavioral QLTL, which is a “behavioral” vari...
We address two central notions of fairness in the literature of planning...
In synthesis, assumptions are constraints on the environment that rule o...
We study the characterization and computation of general policies for
fa...
In Reasoning about Action and Planning, one synthesizes the agent plan b...
MDPs extended with LTLf/LDLf non-Markovian rewards have recently attract...
The ability to model continuous change in Reiter's temporal situation
ca...
Manufacturing is transitioning from a mass production model to a
manufac...
In Markov Decision Processes (MDPs), the reward obtained in a state depe...
In this paper, we investigate bounded action theories in the situation
c...
Runtime monitoring is one of the central tasks to provide operational
de...
Description logic Knowledge and Action Bases (KAB) are a mechanism for
p...