A review of attack graph and attack tree visual syntax in cyber security
Perceiving and understanding cyber-attacks can be a difficult task, and more effective
techniques are needed to aid cyber-attack perception. Attack modelling techniques (AMTs) …
techniques are needed to aid cyber-attack perception. Attack modelling techniques (AMTs) …
Challenges and opportunities in deep reinforcement learning with graph neural networks: A comprehensive review of algorithms and applications
Deep reinforcement learning (DRL) has empowered a variety of artificial intelligence fields,
including pattern recognition, robotics, recommendation systems, and gaming. Similarly …
including pattern recognition, robotics, recommendation systems, and gaming. Similarly …
[BOOK][B] An introduction to the planning domain definition language
Planning is the branch of Artificial Intelligence (AI) that seeks to automate reasoning about
plans, most importantly the reasoning that goes into formulating a plan to achieve a given …
plans, most importantly the reasoning that goes into formulating a plan to achieve a given …
A survey on interpretable reinforcement learning
Although deep reinforcement learning has become a promising machine learning approach
for sequential decision-making problems, it is still not mature enough for high-stake domains …
for sequential decision-making problems, it is still not mature enough for high-stake domains …
Learning safe numeric action models
Powerful domain-independent planners have been developed to solve various types of
planning problems. These planners often require a model of the acting agent's actions …
planning problems. These planners often require a model of the acting agent's actions …
The 2014 international planning competition: Progress and trends
Abstract We review the 2014 International Planning Competition (IPC-2014), the eighth in a
series of competitions starting in 1998. IPC-2014 was held in three separate parts to assess …
series of competitions starting in 1998. IPC-2014 was held in three separate parts to assess …
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 …
PROST: Probabilistic planning based on UCT
T Keller, P Eyerich - Proceedings of the International Conference on …, 2012 - ojs.aaai.org
We present PROST, a probabilistic planning system that is based on the UCT algorithm by
Kocsis and Szepesvari (2006), which has been applied successfully to many areas of …
Kocsis and Szepesvari (2006), which has been applied successfully to many areas of …
Probabilistic programs as an action description language
Actions description languages (ADLs), such as STRIPS, PDDL, and RDDL specify the input
format for planning algorithms. Unfortunately, their syntax is familiar to planning experts only …
format for planning algorithms. Unfortunately, their syntax is familiar to planning experts only …
[HTML][HTML] The actorʼs view of automated planning and acting: A position paper
Planning is motivated by acting. Most of the existing work on automated planning
underestimates the reasoning and deliberation needed for acting; it is instead biased …
underestimates the reasoning and deliberation needed for acting; it is instead biased …