Interactive Planning-Based Hypothesis Generation with LTS++

Authors: Shirin Sohrabi, Octavian Udrea, Anton V. Riabov, Oktie Hassanzadeh

IJCAI 2016 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Experimental We have evaluated several algorithms for this purpose, and currently use the k-shortest path algorithm K [Aljazzar and Leue, 2011]. To test the model, a sequence of observations can be entered by clicking on Next: edit trace from the LTS++ IDE main page. The tool automatically generates planning problems from the LTS++ specification and entered trace. The generated hypotheses are the result of running a planner and finding the most plausible hypotheses ranked by plausibility from highest to lowest. Figure 2 shows an example of hypotheses generated for the critical care model; the result is automatically generated by our tool.
Researcher Affiliation Industry IBM T.J. Watson Research Center 1101 Kitchawan Rd, Yorktown Heights, NY 10598, USA {ssohrab, udrea, riabov, hassanzadeh}@us.ibm.com
Pseudocode No The paper does not include any pseudocode or algorithm blocks.
Open Source Code No The paper does not provide any links to source code or explicitly state that the code for LTS++ is open-source or publicly available.
Open Datasets No The paper mentions using a 'critical care model' and 'historical observations' but does not provide any concrete access information (link, DOI, specific citation, or repository) for any dataset used in its evaluation.
Dataset Splits No The paper does not provide specific details on dataset splits (e.g., percentages, sample counts, or cross-validation setup) for training, validation, or testing.
Hardware Specification No The paper does not mention any specific hardware (e.g., CPU, GPU models, or memory specifications) used for running the experiments or the LTS++ system.
Software Dependencies No The paper mentions several components and algorithms like PDDL and the k-shortest path algorithm K [Aljazzar and Leue, 2011], but does not provide specific version numbers for any software dependencies.
Experiment Setup No The paper describes the functionality of the LTS++ IDE and how it's used for testing models (e.g., 'a sequence of observations can be entered'), but it does not provide explicit experimental setup details like hyperparameters, training configurations, or other system-level settings used for the evaluations presented in the paper.