What is recorded here?
Learns a team action-value as a sum of agent-local utilities from one shared reward, enabling centralized training and decentralized greedy execution.
Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.
Scientific scope
Additive factorization restricts the representable joint value functions; the learned utilities are not separately observed per-agent rewards. Reported advantages concern the paper's partially observed cooperative tasks.
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People and systems
Peter Sunehag; Guy Lever; Audrunas Gruslys; Wojciech Marian Czarnecki; Vinicius Zambaldi; Max Jaderberg; Marc Lanctot; Nicolas Sonnerat; Joel Z. Leibo; Karl Tuyls; Thore Graepel
Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.
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English catalogue narrative
Value-Decomposition Networks for cooperative multi-agent learning
Learns a team action-value as a sum of agent-local utilities from one shared reward, enabling centralized training and decentralized greedy execution.
Scientific scope
Additive factorization restricts the representable joint value functions; the learned utilities are not separately observed per-agent rewards. Reported advantages concern the paper's partially observed cooperative tasks.
Reading status
This is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.
People and systems
Peter Sunehag; Guy Lever; Audrunas Gruslys; Wojciech Marian Czarnecki; Vinicius Zambaldi; Max Jaderberg; Marc Lanctot; Nicolas Sonnerat; Joel Z. Leibo; Karl Tuyls; Thore Graepel
Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.