Self-organising vocabularies

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Multiagent Learning: Basics, Challenges, and Prospects (2012, background): “Some work has already successfully explored the integration of learning in these realworld domains and has shown promising results that justify a stronger focus by the community on complex systems; for example, see Richter, Aberdeen, and Yu (2006); Kalyanakrishnan, Liu, and Stone (2006); Abbeel et a”
Symbol grounding and the symbolic theft hypothesis (2002, unknown): “For example, in models that study the auto-organization of signalmeaning tables (e.g., Steels, 1996; Oliphant and Batali, 1997), the researchers provide the system with a fixed list of N symbols denoting " meanings " and M symbolsdenotingcommunicationsignals.”
Learning Communication for Multi-agent Systems (2002, background): “[4] show that vocabulary can evolve through the principle of self-organization.”
Cooperative Multi-Agent Learning: The State of the Art (2005, background): “Similar approaches to evolving communication languages are presented in [215, 217, 218, 195, 57, 219, 220, 42].”
Minimal Requirements for the Emergence of Learned Signaling (2014, methodology): “To this end, he uses a modiﬁed association-based model (based on Steels, 1997) which employs a “ stay/switch ” strategy — agents stick to successful strategies with some chance of switching to less successful ones.”