{"doi":"10.1145/3490486.3538330","title":"Optimal Correlated Equilibria in General-Sum Extensive-Form Games: Fixed-Parameter Algorithms, Hardness, and Two-Sided Column-Generation","abstract":"We study the problem of finding optimal correlated equilibria of various sorts in extensive-form games: normal-form coarse correlated equilibrium (NFCCE), extensive-form coarse correlated equilibrium (EFCCE), and extensive-form correlated equilibrium (EFCE). We make two primary contributions. First, we introduce a new algorithm for computing optimal equilibria in all three notions. Its runtime depends exponentially only on a parameter related to the information structure of the game. We also prove a fundamental complexity gap between NFCCE and the other two concepts. Second, we propose a two-sided column generation approach for use when the runtime or memory usage of the previous algorithm is prohibitive. Our algorithm improves upon an earlier one-sided approach by means of a new decomposition of correlated strategies which allows players to reoptimize their sequence-form strategies with respect to correlation plans which were previously added to the support. Experiments show that our techniques outperform the prior state of the art for computing optimal general-sum correlated equilibria. Funding: This work was supported by National Institutes of Health [Grant A240108S001]; Vannevar Bush Faculty Fellowship [Grant ONR N00014-23-1-2876]; National Science Foundation [Grants CCF-173355, IIS-190140, RI-1901403, RI-2312342]; and Army Research Office [Grants W911NF2010081, W911NF2210266].","journal":"Mathematics of Operations Research","year":2022,"id":301109,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":2,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9519,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2022-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":602130,"name":"Gabriele Farina","orcid":"0000-0002-3976-0061","position":1,"is_corresponding":false},{"id":991975,"name":"Andrea Celli","orcid":"0000-0002-2046-4019","position":2,"is_corresponding":false},{"id":732860,"name":"Tüomas Sandholm","orcid":"0000-0001-8861-9366","position":3,"is_corresponding":false},{"id":117873,"name":"Brian Zhang","orcid":null,"position":0,"is_corresponding":true}],"reference_count":19,"raw_metadata":null,"created_at":"2026-07-19T00:31:57.812980Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}