A review of learning planning action models
Automated planning has been a continuous field of study since the 1960s, since the notion
of accomplishing a task using an ordered set of actions resonates with almost every known …
of accomplishing a task using an ordered set of actions resonates with almost every known …
MACQ: a holistic view of model acquisition techniques
E Callanan, R De Venezia, V Armstrong… - arXiv preprint arXiv …, 2022 - arxiv.org
For over three decades, the planning community has explored countless methods for data-
driven model acquisition. These range in sophistication (eg, simple set operations to full …
driven model acquisition. These range in sophistication (eg, simple set operations to full …
Interactive narrative and story-telling
R Aylett - The Handbook on Socially Interactive Agents: 20 years …, 2022 - dl.acm.org
The creation and telling of stories is thought to be a basic human characteristic. All societies
we know of have stories as part of their culture, with dramatic enaction and recitation—often …
we know of have stories as part of their culture, with dramatic enaction and recitation—often …
Discovering relational and numerical expressions from plan traces for learning action models
In this paper, we propose a domain learning process build on a machine learning-based
process that, starting from plan traces with (partially known) intermediate states, returns a …
process that, starting from plan traces with (partially known) intermediate states, returns a …
Ascol: A tool for improving automatic planning domain model acquisition
Intelligent agents solving problems in the real world require domain models containing
widespread knowledge of the world. AI Planning requires domain models. Synthesising …
widespread knowledge of the world. AI Planning requires domain models. Synthesising …
Validating domains and plans for temporal planning via encoding into infinite-state linear temporal logic
Temporal planning is an active research area of Artificial Intelligence because of its many
applications ranging from roboticsto logistics and beyond. Traditionally, authors focused on …
applications ranging from roboticsto logistics and beyond. Traditionally, authors focused on …
In defence of design patterns for AI planning knowledge models
M Vallati, TL McCluskey - … Conference of the Italian Association for Artificial …, 2020 - Springer
Abstract Design patterns are widely used in various areas of computer science, the most
notable example being software engineering. They have been introduced also for …
notable example being software engineering. They have been introduced also for …
Action Model Learning based on Regular Grammar Induction for AI Planning
M Grand - 2022 - theses.hal.science
The field of artificial intelligence aims to design and build autonomous agents able to
perceive, learn and act without any human intervention to perform complex tasks. To perform …
perceive, learn and act without any human intervention to perform complex tasks. To perform …
Work in Progress--Automated Generation of Robotic Planning Domains from Observations
M Diehl, K Ramirez-Amaro - arXiv preprint arXiv:2107.04614, 2021 - arxiv.org
In this paper, we report the results of our latest work on the automated generation of
planning operators from human demonstrations, and we present some of our future research …
planning operators from human demonstrations, and we present some of our future research …
[PDF][PDF] Acquiring Process Knowledge in Hybrid Planning Domains using Machine Learning
Abstract Recent progress in Automated Planning not only involves improvements in the
efficiency of planning engines but also in the granularity in which domains can be modelled …
efficiency of planning engines but also in the granularity in which domains can be modelled …