What is recorded here?
Combined off-policy deep reinforcement learning of approximate best responses with supervised reservoir-memory learning of average behavior, supporting end-to-end imperfect-information self-play.
Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.
Scientific scope
Extends fictitious play/FSP and inherits DQN/reservoir sampling. Approximate neural best responses and finite buffers do not inherit exact fictitious-play convergence automatically; source results concern specified Leduc/limit-hold'em settings, not all multiplayer games.
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People and systems
Johannes Heinrich; David Silver
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
Neural fictitious self-play
Combined off-policy deep reinforcement learning of approximate best responses with supervised reservoir-memory learning of average behavior, supporting end-to-end imperfect-information self-play.
Scientific scope
Extends fictitious play/FSP and inherits DQN/reservoir sampling. Approximate neural best responses and finite buffers do not inherit exact fictitious-play convergence automatically; source results concern specified Leduc/limit-hold'em settings, not all multiplayer games.
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
Johannes Heinrich; David Silver
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.