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Abstract : |
The last twenty years of AI planning research has discovered a wide variety of planning techniques such as state-space search, hierarchical planning, case-based planning and reactive planning. These techniques have been implemented in numerous planning systems (e.g., [12, 8, 9, 10, 11]). Initially, a number of simple toy domains have been devised to assist in the analysis and evaluation of planning systems and techniques. The most well known examples are "Blocks World " and "Towers of Hanoi. " As planning systems grow in sophistication and capabilities, however, there is a clear need for planning benchmarks with matching complexity to evaluate those new features and capabilities. UM Translog is a planning domain designed specifically for this purpose. UM Translog was inspired by the CMU Transport Logistics domain developed by Manuela Veloso. UM Translog is an order of magnitude larger in size (41 actions versus 6), number of features and types interactions. It provides a rich set of entities, attributes, actions and conditions, which can be used to specify rather complex planning problems with a variety of plan interactions. The detailed set of operators provides long plans ( ~ 40 steps) with many possible, |
