Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in [1]
Automaton Plans
Authors: C. Bäckström, A. Jonsson, P. Jonsson
JAIR 2014 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | In this paper we introduce a novel solution concept called automaton plans in which plans are represented using hierarchies of automata. Automaton plans can be viewed as an extension of macros that enables parameterization and branching. We provide several examples that illustrate how automaton plans can be useful, both as a compact representation of exponentially long plans and as an alternative to sequential solutions in benchmark domains such as LOGISTICS and GRID. We also compare automaton plans to other compact plan representations from the literature, and find that automaton plans are strictly more expressive than macros, but strictly less expressive than HTNs and certain representations allowing efficient sequential access to the operators of the plan. A formalization of automaton plans using Mealy machines, providing a stronger theoretical foundation of automaton plans in automaton theory. A proof that plan verification for automaton plans is Πp 2-complete, a result that is used to compare the expressive power of automaton plans to that of other compact plan representations. A reduction from automaton plans to HTNs, proving that HTNs are strictly more expressive than automaton plans, which comes at the price of more expensive computational properties. |
| Researcher Affiliation | Academia | Christer Bäckström EMAIL Department of Computer Science Linköping University SE-581 83 Linköping, Sweden Anders Jonsson EMAIL Dept. Information and Communication Tecnologies Universitat Pompeu Fabra Roc Boronat 138 08018 Barcelona, Spain Peter Jonsson EMAIL Department of Computer Science Linköping University SE-581 83 Linköping, Sweden |
| Pseudocode | Yes | Figure 7: Algorithm for using an automaton plan as a CRAR. Figure 8: Algorithm for finding the next operator of an automaton plan. Figure 9: Algorithm that always selects the applicable operator with lowest index. |
| Open Source Code | No | The paper does not contain any statements or links indicating that source code for the described methodology is publicly available. |
| Open Datasets | No | We provide several examples that illustrate how automaton plans can be useful, both as a compact representation of exponentially long plans and as an alternative to sequential solutions in benchmark domains such as LOGISTICS and GRID. The paper uses standard benchmark domains for illustrative purposes but does not utilize specific datasets for empirical evaluation that require public access information. |
| Dataset Splits | No | The paper does not use specific datasets for empirical evaluation, hence no dataset split information is provided. |
| Hardware Specification | No | The paper presents theoretical work and does not report experimental results that would require hardware specifications. |
| Software Dependencies | No | The paper presents theoretical work and does not specify software dependencies with version numbers for experimental reproducibility. |
| Experiment Setup | No | The paper presents theoretical work and does not describe any experimental setup, hyperparameters, or training configurations. |