{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/constrained-optimization-under-uncertainty","title":"Constrained optimization under uncertainty for decision-making problems: Application to Real-Time Strategy games","arxiv_id":"1901.00942","date":"2019-01-03","proceeding":null,"authors":["Valentin Antuori","Florian Richoux"],"abstract":"Decision-making problems can be modeled as combinatorial optimization\nproblems with Constraint Programming formalisms such as Constrained\nOptimization Problems. However, few Constraint Programming formalisms can deal\nwith both optimization and uncertainty at the same time, and none of them are\nconvenient to model problems we tackle in this paper.\n  Here, we propose a way to deal with combinatorial optimization problems under\nuncertainty within the classical Constrained Optimization Problems formalism by\ninjecting the Rank Dependent Utility from decision theory. We also propose a\nproof of concept of our method to show it is implementable and can solve\nconcrete decision-making problems using a regular constraint solver, and\npropose a bot that won the partially observable track of the 2018 {\\mu}RTS AI\ncompetition.\n  Our result shows it is possible to handle uncertainty with regular Constraint\nProgramming solvers, without having to define a new formalism neither to\ndevelop dedicated solvers. This brings new perspective to tackle uncertainty in\nConstraint Programming.","url_abs":"http://arxiv.org/abs/1901.00942v3","url_pdf":"http://arxiv.org/pdf/1901.00942v3.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"constrained-optimization-under-uncertainty","repo_url":"https://github.com/richoux/microrts-uncertainty","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"combinatorial-optimization","task_name":"Combinatorial Optimization"},{"task_slug":"decision-making","task_name":"Decision Making"},{"task_slug":"real-time-strategy-games","task_name":"Real-Time Strategy Games"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}