Learning to signal: Analysis of a micro-level reinforcement model

DOI10.1016/j.spa.2008.02.014zbMath1166.60044OpenAlexW2149820942MaRDI QIDQ1004397

Brian Skyrms, Stanislav Volkov, Raffaele Argiento, Robin Pemantle

Publication date: 10 March 2009

Published in: Stochastic Processes and their Applications (Search for Journal in Brave)

Full work available at URL: https://lup.lub.lu.se/record/4588099

zbMATH Keywords

signalingevolutionary game theoryincomplete informationGame theoryurn model

Mathematics Subject Classification ID

2-person games (91A05) Applications of Markov chains and discrete-time Markov processes on general state spaces (social mobility, learning theory, industrial processes, etc.) (60J20) Signaling and communication in game theory (91A28)

Related Items (17)

Evolutionary game theory: a renaissance ⋮ Wisdom of crowds versus groupthink: learning in groups and in isolation ⋮ Inventing new signals ⋮ How signaling conventions are established ⋮ Some dynamics of signaling games ⋮ The evolution of compositionality in signaling games ⋮ Compositional signaling in a complex world ⋮ Probe and adjust in information transfer games ⋮ David Lewis in the lab: experimental results on the emergence of meaning ⋮ Emergence of information transfer by inductive learning ⋮ Stein's Method for the Beta Distribution and the Pólya-Eggenberger Urn ⋮ Bidirectional optimization from reasoning and learning in games ⋮ Evolutionary dynamics of Lewis signaling games: Signaling systems vs. partial pooling ⋮ Signaling Games ⋮ Pragmatics, Logic and Information Processing ⋮ On salience and signaling in sender-receiver games: partial pooling, learning, and focal points ⋮ The role of forgetting in the evolution and learning of language

Cites Work

• Nonconvergence to unstable points in urn models and stochastic approximations
• A survey of random processes with reinforcement
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• Stochastic algorithms
• Asymptotics of a matrix valued Markov chain arising in sociology.
• Time to absorption in discounted reinforcement models.
• On Sequential Designs for Maximizing the Sum of $n$ Observations
• The Randomized Play-the-Winner Rule in Medical Trials
• A dynamic model of social network formation
• Unnamed Item

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