Signals: evolution, learning, and information

By Armin W. Schulz. 2012

389 citations recorded by the source corpus.

Subfields: Genetics, Management Science and Operations Research, Sociology and Political Science

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Citations in the corpus

Multi-Agent Cooperation and the Emergence of (Natural) Language (2016, methodology): “We leverage ideas from work in linguistics, cognitive science and game theory on the emergence of language (Wagner et al., 2003; Skyrms, 2010; Crawford & Sobel, 1982; Crawford, 1998).”
Multiagent cooperation and competition with deep reinforcement learning (2015, background): “A future direction of the present approach is to study of how communication codes [27, 28] and consensus [28–30] can emerge between interacting agents in complex environments without any a priori agreements, rules, or even high-level concepts of themselves and their environment.”
Emergence of Linguistic Communication from Referential Games with Symbolic and Pixel Input (2018, background): “In classic signaling games, this polysemy phenomenon manifests itself as different states receiving the same signal and is termed partial pooling equilibrium (Skyrms, 2010).”
Iterated learning for emergent systematicity in VQA (2021, background): “In these games, one agent must describe what it saw to another agent, which is tasked with figuring out what the first agent saw (Lewis, 2008; Skyrms, 2010; Steels & Loetzsch, 2012).”
Origins of Meaning: Must We 'Go Gricean'? (2013, background): “…peacocks’ tail displays, birdsongs, dolphins’ ‘signature whistles’, and so on).17 In recent years, considerable progress has been made accounting for these sorts of signals using the theoretical apparatus of Evolutionary Game Theory (EGT) (see Maynard Smith and Harper, 2003, and Skyrms, 2010).”
False Information on Web and Social Media: A Survey (2018, background): “Thus, understanding the motives for disinformation are much akin to understanding the motives for deception [25, 93].”