On the Effective Configuration of Planning Domain Models

The development of domain-independent planners This modular approach also supports the use of reformulation within the AI Planning community is leading to and configuration techniques which can automatically "off the shelf" technology that can be used in a reformulate, re-represent or tune the domain model and/or wide range of applications. Moreover, it allows a problem description in order to increase the efficiency of modular approach - in which planners and domain a planner and increase the scope of problems solved. The knowledge are modules of larger software applications idea is to make these techniques to some degree independent - that facilitates substitutions or improvements of domain and planner (that is, applicable to a range of individual modules without changing the of domains and planning engine technologies), and use them rest of the system. This approach also supports the to form a wrapper around a planner, improving its overall use of reformulation and configuration techniques, performance for the domain to which it is applied. Types which transform how a model is represented in order of reformulation include macro-learning [Botea et al., 2005; to improve the efficiency of plan generation. Newton et al., 2007], action schema splitting [Areces et al., In this paper, we investigate how the performance 2014] and entanglements [Chrpa and McCluskey, 2012]: here of planners is affected by domain model configuration.