Signals: Evolution, Learning, and InformationBrian Skyrms presents a fascinating exploration of how fundamental signals are to our world. He uses a variety of tools -- theories of signaling games, information, evolution, and learning -- to investigate how meaning and communication develop. He shows how signaling games themselves evolve, and introduces a new model of learning with invention. The juxtaposition of atomic signals leads to complex signals, as the natural product of gradual process. Signals operate in networks of senders and receivers at all levels of life. Information is transmitted, but it is also processed in various ways. That is how we think -- signals run around a very complicated signaling network. Signaling is a key ingredient in the evolution of teamwork, in the human but also in the animal world, even in micro-organisms. Communication and co-ordination of action are different aspects of the flow of information, and are both effected by signals. |
Contents
Signals 2 Signals in Nature | |
Information | |
Evolution | |
Evolution in Lewis Signaling Games | |
Deception | |
Learning | |
Learning in Lewis Signaling Games | |
Inventing New Signals | |
Logic and Information Processing | |
Complex Signals and Compositionality | |
Teamwork | |
Learning to Network | |
Postscript | |
References | |
Synonyms Bottlenecks Category Formation | |
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alarm calls Animal average payoff bacteria ball basic best response biological Bush-Mosteller Cambridge Chapter chickadee Chinese restaurant process complex signals consider cooperative deception decision problem Democritus Diana monkeys differential reproduction Empedocles equilibrium equiprobable Erev evolution of signaling evolutionarily stable strategy evolve example Figure guests Hawk Hofbauer Huttegger individuals informational content initial weights interactions invention Journal Kula Kula ring Language Law of Effect learn to signal leopard Lewis signaling game logic Mathematical Maynard Smith misinformation monkeys moves the probability mutation natural salience nature chooses network formation number of signals optimal partial pooling partition Pemantle play players Pólya urn pooling equilibria population possible predator probe and adjust quantity of information quorum-sensing random receiver’s reinforcement learning replicator dynamics ring rock-scissors-paper Roth-Erev reinforcement send signal sender and receiver sender observes sender-receiver sender’s strategy signaling networks signaling system simulations Skyrms species spontaneously Stochastic structure Suppose synonyms theory University Press unstable vervets zero