Stability of Multi-Agent Learning in Competitive Networks: Delaying the Onset of Chaos
Aamal Hussain,
Francesco Belardinelli
Abstract:The behaviour of multi agent learning in competitive network games is often studied within the context of zero sum games, in which convergence guarantees may be obtained. However, outside of this class the behaviour of learning is known to display complex behaviours and convergence cannot be always guaranteed. Nonetheless, in order to develop a complete picture of the behaviour of multi agent learning in competitive settings, the zero sum assumption must be lifted.
Motivated by this we study the Q Learning dyn… Show more
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