{"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/rinascimento-optimising-statistical-forward","title":"Rinascimento: Optimising Statistical Forward Planning Agents for Playing Splendor","arxiv_id":"1904.01883","date":"2019-04-03","proceeding":null,"authors":["Ivan Bravi","Simon Lucas","Diego Perez-Liebana","Jialin Liu"],"abstract":"Game-based benchmarks have been playing an essential role in the development\nof Artificial Intelligence (AI) techniques. Providing diverse challenges is\ncrucial to push research toward innovation and understanding in modern\ntechniques. Rinascimento provides a parameterised partially-observable\nmultiplayer card-based board game, these parameters can easily modify the\nrules, objectives and items in the game. We describe the framework in all its\nfeatures and the game-playing challenge providing baseline game-playing AIs and\nanalysis of their skills. We reserve to agents' hyper-parameter tuning a\ncentral role in the experiments highlighting how it can heavily influence the\nperformance. The base-line agents contain several additional contribution to\nStatistical Forward Planning algorithms.","url_abs":"http://arxiv.org/abs/1904.01883v1","url_pdf":"http://arxiv.org/pdf/1904.01883v1.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":"rinascimento-optimising-statistical-forward","repo_url":"https://github.com/ivanbravi/RinascimentoFramework","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}