# game: balance exploration and exploitation, making decisions cooperatively without sharing information.

<< Multiagent reinforcement learning (MARL) studies crucial principles that are applicable to a variety of fields, including wireless networking and autonomous driving. (AA) propose a photonic-based decision-making algorithm to address one of the most fundamental problems in MARL, called the competitive multiarmed bandit (CMAB) problem. >>

AA << demonstrate that chaotic oscillations and cluster synchronization of optically coupled lasers, along with (their) proposed decentralized coupling adjustment, efficiently balance exploration and exploitation while facilitating cooperative decision making without explicitly sharing information among agents. >>

AA << study demonstrates how decentralized reinforcement learning can be achieved by exploiting complex physical processes controlled by simple algorithms. >>

Shun Kotoku, Takatomo Mihana, et al. Decentralized multiagent reinforcement learning algorithm using a cluster-synchronized laser network. Phys. Rev. E 110, 064212. Dec 11, 2024.

https://journals.aps.org/pre/abstract/10.1103/PhysRevE.110.064212

Img: https://x.com/PhysRevE/status/1866889144657465632

Also: game, chaos, ai (artificial intell), in https://www.inkgmr.net/kwrds.html 

Keywords: game, cooperation, chaos, exploration, exploitation, ai, artificial intelligence, MARL, CMAB.

# gst: like a bowl of worms, but with two behavioral regimes

AA << have observed strand motion in a polymer melt that contradicts the idea of independent motion. >>️

<< According to the results of new neutron scattering experiments, polymer molecules in plastics move in ways that aren’t captured by commonly used models. >>

<< Melt a plastic, and its constituent molecules, known as polymers, wiggle around. Experts typically describe polymer motion using the so-called tube model, which imagines plastics as a tangle of polymer strands—think a bowlful of worms. The model assumes that each strand moves independently within a virtual tube.  >>️

<< Monitoring the center of mass motion of the short strands, they observed two behavior regimes. For short translational distances, the motion of the short strands slowed as they grew apart. For longer distances, when the center of mass of the strands reached a size on the order of the diameter of the virtual tube, the speed at which the short strands moved stopped slowing down and instead matched that of diffusion. (..) the motions of short strands were tied to those of neighboring strands at short distances, differing from a standard assumption of the tube model. This cooperative motion may come from interactions between the segments, beyond simple local friction. >>️️

Sophia Chen. The Weird Wiggle of Polymers. Physics 14, s56. May 4, 2021.

https://physics.aps.org/articles/v14/s56    

Zamponi M., Kruteva M., et al. Cooperative Chain Dynamics of Tracer Chains in Highly Entangled Polyethylene Melts. Phys. Rev. Lett. 126, 187801. May 4,  2021.

https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.126.187801