A Simple Framework for Cognitive Planning

Authors: Jorge Luis Fernandez Davila, Dominique Longin, Emiliano Lorini, Frédéric Maris6331-6339

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Reproducibility Variable Result LLM Response
Research Type Theoretical We present a novel approach to cognitive planning... We encode the cognitive planning problem in an epistemic logic... We study a NP-fragment of the logic whose satisfiability problem is reduced to SAT. We provide complexity results for the cognitive planning problem. Moreover, we illustrate its potential for applications in human-machine interaction... We have studied both complexity of satisfiability for the logic and complexity of the cognitive planning problem. Our approach relies on SAT, given the NP-completeness of the satisfiability problem for the epistemic language we consider.
Researcher Affiliation Academia Jorge Luis Fernandez Davila,1 Dominique Longin,2 Emiliano Lorini,2 Fr ed eric Maris1 1IRIT, Toulouse University, France 2IRIT, CNRS, Toulouse University, France
Pseudocode No The paper presents a formal logical framework, definitions, and theorems, but it does not include any structured pseudocode or algorithm blocks.
Open Source Code No We are currently implementing a cognitive planning algorithm using a SATsolver as well as the HMI scenario we presented in the paper.
Open Datasets No This is a theoretical paper that introduces a logical framework and studies its complexity. It does not use or reference any publicly available datasets for training or evaluation.
Dataset Splits No The paper is theoretical and does not involve empirical experiments with data, therefore, no training, validation, or test dataset splits are described.
Hardware Specification No The paper is theoretical and focuses on a logical framework and its complexity. It does not describe any specific hardware used for experiments or computations.
Software Dependencies No The paper is theoretical and does not describe any specific software dependencies or version numbers. It mentions 'a SAT-solver' for future implementation, but without version details.
Experiment Setup No The paper is theoretical and focuses on a logical framework, definitions, and complexity results. It does not describe any experimental setup details, hyperparameters, or training configurations.