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 …
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 …
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 …
S Ware, RM Young - Proceedings of the AAAI Conference on Artificial …, 2014 - ojs.aaai.org
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 …
Quantitative formal models capture probabilistic behaviour, real-time aspects, or general continuous dynamics. A number of tools support their automatic analysis with respect to …
The Atari 2600 games supported in the Arcade Learning Environment (Bellemare et al. 2013) all feature a known initial (RAM) state and actions that have deterministic effects …
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 …