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0111 · Dec 201919922001200920172026
4 results for reset-free

New framework finds periodic policies in reset-free MDPs with sublinear regret.

problem Reset-free reinforcement learning with unknown dynamics and terminal law constraints.
method Periodic framework, periodic policies, periodic regret.
result First non-asymptotic guarantees for reset-free learning in multi-agent settings.

We study learning control in an online reset-free lifelong learning scenario, where mistakes can compound catastrophically into the future and the underlying dynamics of the environment may change. Traditional model-free policy learning methods have achieved successes in difficult tasks due to their broad flexibility, …

2019-12-03abs ↗pdf ↗

Optimal threshold resetting reduces search time for multiple diffusive searchers.

problem Optimizing search time for multiple diffusive searchers in a one-dimensional space.
method Threshold resetting (TR) is introduced as an event-driven optimization strategy, coupling resetting to the internal dynamics of searchers.
result Optimal threshold distance uu significantly reduces mean first-passage time for N2N \geq 2 searchers, with a minimum at Nopt(u)N_{\mathrm{opt}}(u).