Jun 8, 2012 · Break with agents who listen to too many others. (at least when making Boolean decisions!) (Extended Abstract). Daniel Epstein, Ana L. C. ...
Break with agents who listen to too many others. (at least when making Boolean decisions!) (Extended Abstract). Daniel Epstein, Ana L. C. Bazzan, and André M ...
The results using preferential attachments and random Boolean networks show that an efficient equilibrium can be achieved, provided agents do ...
Our results using preferential attachments and random Boolean networks show that an efficient equilibrium can be achieved, provided agents do experimentation.
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Break with agents who listen to too many others (at least when making Boolean decisions!). Daniel Epstein Ana L. C. Bazzan André M. Machado.
Daniel Epstein, Ana L. C. Bazzan, André M. Machado: Break with agents who listen to too many others (at least when making Boolean decisions!)
Bazzan, A.L.C., Epstein, D., Machado, A.M.: Break with agents who listen to too many others (at least when making Boolean decisions!). In: Proceedings of ...
Break with agents who listen to too many others (at least when making Boolean decisions!) · Computer Science. Adaptive Agents and Multi-Agent Systems · 2012.
Break with agents who listen to too many others (at least when making Boolean decisions!) Conference Paper. Full-text available. Jun 2012.
Multi-agent systems. Recommendations. Break with agents who listen to too many others (at least when making Boolean decisions!) AAMAS '12: Proceedings of the ...