Multi-Tier Automated Planning for Adaptive Behavior

Daniel Ciolek, Nicolás D'Ippolito, Alberto Pozanco, Sebastian Sardiña

PosterID: 10
picture_as_pdf PDF
library_books Slides
library_books Poster
menu_book BibTeX
A planning domain, as any model, is never “complete” and inevitably makes assumptions on the environment's dynamic. By allowing the specification of just one domain model, the knowledge engineer is only able to make one set of assumptions, and to specify a single objective-goal. Borrowing from work in Software Engineering, we propose a multi-tier framework for planning that allows the specification of different sets of assumptions, and of different corresponding objectives. The framework aims to support the synthesis of adaptive behavior so as to mitigate the intrinsic risk in any planning modeling task. After defining the multi-tier planning task and its solution concept, we show how to solve problem instances by a succinct compilation to a form of non-deterministic planning. In doing so, our technique justifies the applicability of planning with both fair and unfair actions, and the need for more efforts in developing planning systems supporting dual fairness assumptions.

Session Aus1: Non-deterministic & Probabilistic Planning
Canb 10/27/2020, 20:00 – 21:00
10/30/2020, 11:00 – 12:00
Paris 10/27/2020, 10:00 – 11:00
10/30/2020, 01:00 – 02:00
NYC 10/27/2020, 05:00 – 06:00
10/29/2020, 20:00 – 21:00
LA 10/27/2020, 02:00 – 03:00
10/29/2020, 17:00 – 18:00