Oversubscription Planning (OSP) value landmarks

Technical Report for the Paper on Value Driven Landmarks for Oversubscription Planning

A detailed technical report of out ICAPS 2018 paper Value Driven Landmark for Oversubscription Planning is available. In the technical report, we provide detail examples of the theory in the paper. We look closely at the terms of optimality and achievements concerning the complexity of the real-world scenarios. ICAPS 2018 Slides of our presentation along with supplementary material can be found at the publication page.
Starting with the most fundamental question of what additive utility function in OSP problem is, we point out the challenges in multi-valued planning tasks with additive utility setting. We discuss the relationships between state variables and different value assignments to a variable in successive states along a plan. We closely consider negative interactions between state variables with multi-valued (non-zero binary) utility setting, and we show how these negative interactions could occur in tasks with non-negative utility setting.
We treat the OSP task as a process of improvement of the initial state rather than a process of collecting valuable facts is the most basic fundamental of our approach. In contrast to classical planning and partial satisfaction problems where there is one explicit assignment for each variable that is defined as valuable, OSP with additive utility functions allows for each variable to be associated with a set of different utilities. Thus, in the additive utility case, a variable assignment is valuable if its utility is better than the utility at the initial state, where an optimal solution will be the maxima(red circle) l utility over all variables that are {\em mutually consistent}. Therefore, it is easy to see that the concept of {\em improving states} rather than collecting valuable facts is much more suitable for the general case.
In order to capture the properties of the process, we define the net and gross term for the utility of actions which allow us to evaluate achievements with relative terms within the ongoing process of utility maximization. Each process that improves utility must agree with a few several structural properties of optimal. We can define these properties over process due to the definition of the net and gross actions. Finally, we represent these properties with Value-Driven Landmarks, These Value Landmarks are domain-independent (can be applied in each task if sequential decisions or actions), and lead to better performance, sometimes, as you can see in the attached image, without a search at all.
The red circle emphasizes the tasks that solved without search since no plan that meets optimal properties as applicable. In real-world scenarios that involve budget thus is very likely to happen at some point during the search.
Oversubscription action planning with value landmarks - Empirical evaluation of the improving approach

Oversubscription action planning with value landmarks – Empirical evaluation of the improving approach

Stay tuned, we will keep update here the progress of our research and if you find that problem interesting, let us know, there is a lot of work and we will be more than happy to collaborate.

We will soon post a call for collaboration with some of our suggestions.


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