TY - JOUR
T1 - Representing and planning with interacting actions and privacy
AU - Shekhar, Shashank
AU - Brafman, Ronen I.
N1 - Funding Information:
We thank the reviewers for their useful comments and Daniel Furelos-Blanco, Guillem Frances, and Anders Jonsson for allowing us to use their code as a basis of our implementation. This work was supported by ISF Grants 933/13 and 1651/19 , by the Israel Ministry of Science and Technology Grant 54178 , by the Helmsley Charitable Trust through the Agricultural, Biological and Cognitive Robotics Center of Ben-Gurion University of the Negev , and by the Lynn and William Frankel Center for Computer Science .
Publisher Copyright:
© 2019 Elsevier B.V.
PY - 2020/1/1
Y1 - 2020/1/1
N2 - Interacting actions – actions whose joint effect differs from the union of their individual effects – are challenging both to represent and to plan with due to their combinatorial nature. So far, there have been few attempts to provide a succinct language for representing them that can also support efficient centralized planning and distributed privacy preserving planning. In this paper we suggest an approach for representing interacting actions succinctly and show how such a domain model can be compiled into a standard single-agent planning problem as well as to privacy preserving multi-agent planning. We test the performance of our method on a number of novel domains involving interacting actions and privacy.
AB - Interacting actions – actions whose joint effect differs from the union of their individual effects – are challenging both to represent and to plan with due to their combinatorial nature. So far, there have been few attempts to provide a succinct language for representing them that can also support efficient centralized planning and distributed privacy preserving planning. In this paper we suggest an approach for representing interacting actions succinctly and show how such a domain model can be compiled into a standard single-agent planning problem as well as to privacy preserving multi-agent planning. We test the performance of our method on a number of novel domains involving interacting actions and privacy.
KW - Concurrent interacting actions
KW - Deterministic planning
KW - Distributed privacy preserving planning
KW - Multi-agent planning
UR - http://www.scopus.com/inward/record.url?scp=85074451788&partnerID=8YFLogxK
U2 - 10.1016/j.artint.2019.103200
DO - 10.1016/j.artint.2019.103200
M3 - Meeting Abstract
AN - SCOPUS:85074451788
VL - 278
JO - Artificial Intelligence
JF - Artificial Intelligence
SN - 0004-3702
M1 - 103200
ER -