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Recent works show that continuous communication allows\nefficient training with back-propagation in multi-agent scenarios, but have\nbeen restricted to fully-cooperative tasks. In this paper, we present\nIndividualized Controlled Continuous Communication Model (IC3Net) which has\nbetter training efficiency than simple continuous communication model, and can\nbe applied to semi-cooperative and competitive settings along with the\ncooperative settings. IC3Net controls continuous communication with a gating\nmechanism and uses individualized rewards foreach agent to gain better\nperformance and scalability while fixing credit assignment issues. Using\nvariety of tasks including StarCraft BroodWars explore and combat scenarios, we\nshow that our network yields improved performance and convergence rates than\nthe baselines as the scale increases. Our results convey that IC3Net agents\nlearn when to communicate based on the scenario and profitability.","url_abs":"http://arxiv.org/abs/1812.09755v1","url_pdf":"http://arxiv.org/pdf/1812.09755v1.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":"learning-when-to-communicate-at-scale-in","repo_url":"https://github.com/IC3Net/IC3Net","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"learning-when-to-communicate-at-scale-in","repo_url":"https://github.com/RL-WFU/IC3Net-Highway","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"learning-when-to-communicate-at-scale-in","repo_url":"https://github.com/apsdehal/gym-starcraft","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"starcraft","task_name":"Starcraft"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1812.09755","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1812.09755"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. 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