TY - JOUR
T1 - Heuristic Search For Physics-Based Problems
T2 - 33rd International Conference on Automated Planning and Scheduling, ICAPS 2023
AU - Piotrowski, Wiktor
AU - Sher, Yoni
AU - Grover, Sachin
AU - Stern, Roni
AU - Mohan, Shiwali
N1 - Funding Information:
This work was supported by the DARPA SAIL-ON program under contract HR001120C0040. The views and conclusions in this document are those of the authors and should not be interpreted as representing the official policies, either expressly or implied, of the Defense Advanced Research Projects Agency or the U.S. Government.
Publisher Copyright:
Copyright © 2023, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.
PY - 2023/1/1
Y1 - 2023/1/1
N2 - This paper studies how a domain-independent planner and combinatorial search can be employed to play Angry Birds, a well established AI challenge problem. To model the game, we use PDDL+, a planning language for mixed discrete/continuous domains that supports durative processes and exogenous events. The paper describes the model and identifies key design decisions that reduce the problem complexity. In addition, we propose several domain-specific enhancements including heuristics and a search technique similar to preferred operators. Together, they alleviate the complexity of combinatorial search. We evaluate our approach by comparing its performance with dedicated domain-specific solvers on a range of Angry Birds levels. The results show that our performance is on par with these domain-specific approaches in most levels, even without using our domain-specific search enhancements.
AB - This paper studies how a domain-independent planner and combinatorial search can be employed to play Angry Birds, a well established AI challenge problem. To model the game, we use PDDL+, a planning language for mixed discrete/continuous domains that supports durative processes and exogenous events. The paper describes the model and identifies key design decisions that reduce the problem complexity. In addition, we propose several domain-specific enhancements including heuristics and a search technique similar to preferred operators. Together, they alleviate the complexity of combinatorial search. We evaluate our approach by comparing its performance with dedicated domain-specific solvers on a range of Angry Birds levels. The results show that our performance is on par with these domain-specific approaches in most levels, even without using our domain-specific search enhancements.
UR - http://www.scopus.com/inward/record.url?scp=85169825722&partnerID=8YFLogxK
U2 - 10.1609/icaps.v33i1.27232
DO - 10.1609/icaps.v33i1.27232
M3 - Conference article
AN - SCOPUS:85169825722
SN - 2334-0835
VL - 33
SP - 518
EP - 526
JO - Proceedings International Conference on Automated Planning and Scheduling, ICAPS
JF - Proceedings International Conference on Automated Planning and Scheduling, ICAPS
IS - 1
Y2 - 8 July 2023 through 13 July 2023
ER -