Online judges are systems designed for the reliable evaluation of algorithm source code
submitted by users, which is next compiled and tested in a homogeneous environment …

In this article we introduce the Arcade Learning Environment (ALE): both a challenge
problem and a platform and methodology for evaluating the development of general, domain …

Abstract We review the 2014 International Planning Competition (IPC-2014), the eighth in a
series of competitions starting in 1998. IPC-2014 was held in three separate parts to assess …

Planning is the model-based approach to autonomous behavior where the agent behavior is
derived automatically from a model of the actions, sensors, and goals. The main challenges …

In this paper, we discuss the learning of generalised policies for probabilistic and classical
planning problems using Action Schema Networks (ASNets). The ASNet is a neural network …

Abstract Answer Set Programming (ASP) is a well-established paradigm of declarative
programming that has been developed in the field of logic programming and non-monotonic …

Polynomial-time heuristic functions for planning are commonplace since 20 years. But
polynomial-time in which input? Almost all existing approaches are based on a grounded …

Quantitative formal models capture probabilistic behaviour, real-time aspects, or general
continuous dynamics. A number of tools support their automatic analysis with respect to …

Robots need task planning algorithms to sequence actions toward accomplishing goals that
are impossible through individual actions. Off-the-shelf task planners can be used by …

Glaive is a state-space planner based on Hoffmann and Nebel's Fast-Forward which solves
the narrative planning problem defined by Riedl and Young—to construct a plan which …