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 …
Classical planning in deep latent space: Bridging the subsymbolic-symbolic boundary
M Asai, A Fukunaga - Proceedings of the aaai conference on artificial …, 2018 - ojs.aaai.org
Current domain-independent, classical planners require symbolic models of the problem
domain and instance as input, resulting in a knowledge acquisition bottleneck. Meanwhile …
domain and instance as input, resulting in a knowledge acquisition bottleneck. Meanwhile …
[HTML][HTML] Learning action models with minimal observability
This paper presents FAMA, a novel approach for learning Strips action models from
observations of plan executions that compiles the learning task into a classical planning …
observations of plan executions that compiles the learning task into a classical planning …
Online learning of reusable abstract models for object goal navigation
In this paper, we present a novel approach to incrementally learn an Abstract Model of an
unknown environment, and show how an agent can reuse the learned model for tackling the …
unknown environment, and show how an agent can reuse the learned model for tackling the …
Framer: Planning models from natural language action descriptions
In this paper, we describe an approach for learning planning domain models directly from
natural language (NL) descriptions of activity sequences. The modelling problem has been …
natural language (NL) descriptions of activity sequences. The modelling problem has been …
Learning STRIPS action models with classical planning
This paper presents a novel approach for learning strips action models from examples that
compiles this inductive learning task into a classical planning task. Interestingly, the …
compiles this inductive learning task into a classical planning task. Interestingly, the …
Classical planning in deep latent space
Current domain-independent, classical planners require symbolic models of the problem
domain and instance as input, resulting in a knowledge acquisition bottleneck. Meanwhile …
domain and instance as input, resulting in a knowledge acquisition bottleneck. Meanwhile …
Model-lite planning: Case-based vs. model-based approaches
HH Zhuo, S Kambhampati - Artificial Intelligence, 2017 - Elsevier
There is increasing awareness in the planning community that depending on complete
models impedes the applicability of planning technology in many real world domains where …
models impedes the applicability of planning technology in many real world domains where …
Eliciting and utilising knowledge for security event log analysis: An association rule mining and automated planning approach
S Khan, S Parkinson - Expert Systems with Applications, 2018 - Elsevier
Vulnerability assessment and security configuration activities are heavily reliant on expert
knowledge. This requirement often results in many systems being left insecure due to a lack …
knowledge. This requirement often results in many systems being left insecure due to a lack …
Planning for learning object properties
Autonomous agents embedded in a physical environment need the ability to recognize
objects and their properties from sensory data. Such a perceptual ability is often …
objects and their properties from sensory data. Such a perceptual ability is often …