Tug-of-war model for the two-bandit problem: Nonlocally-correlated parallel exploration via resource conservation

Kim, Song-Ju; Aono, Masashi; Hara, Masahiko

doi:10.1016/j.biosystems.2010.04.002

Cited by 79 publications

(70 citation statements)

References 14 publications

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“…Thus, it is possible to consider that there are nonlocal communications among the nodes in our model with instantaneous information transmissions. In [22][23][24], we reported significances of the nonlocal correlations in enhancing the problem-solving performances.…”

Section: Discussionmentioning

confidence: 98%

A Model of Amoeba-Based Neurocomputer

Aono

Hirata

Hara

et al. 2010

J. Comput. Chem. Jpn.

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Section: Discussionmentioning

confidence: 98%

A Model of Amoeba-Based Neurocomputer

Aono

Hirata

Hara

et al. 2010

J. Comput. Chem. Jpn.

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“…However, the former does not always coincide with the latter in a more general context. In our previous studies [11][12][13][14], we showed that our proposed algorithm called "tug-of-war (TOW) dynamics" is more efficient than other well-known algorithms such as the modified -greedy and softmax algorithms, and is comparable to the "upper confidence bound1-tuned (UCB1T) algorithm", which is known as the best among parameter-free algorithms [15]. Moreover, TOW dynamics effectively adapt to a changing environment wherein the reward probabilities dynamically switch.…”

Section: Introductionmentioning

confidence: 92%

“…Consequently, the TOW dynamics evolve according to a particularly simple rule: in addition to the fluctuation, if machine k is played at each time t, +1 and −ω are added to X k (t) when rewarded and non-rewarded, respectively (Figure 2a). The authors have shown that these simple dynamics gain more rewards (coins or packet transmissions in cognitive radio) than those obtained by other popular algorithms for solving the BP [11][12][13][14]. Many algorithms for the BP estimate the reward probability of each machine.…”

Section: Tow Dynamicsmentioning

confidence: 99%

Harnessing the Computational Power of Fluids for Optimization of Collective Decision Making

2016

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How can we harness nature's power for computations? Our society comprises a collection of individuals, each of whom handles decision-making tasks that are abstracted as computational problems of finding the most profitable option from a set of options that stochastically provide rewards. Society is expected to maximize the total rewards, while the individuals compete for common rewards. Such collective decision making is formulated as the "competitive multi-armed bandit problem (CBP)." Herein, we demonstrate an analog computing device that uses numerous fluids in coupled cylinders to efficiently solve CBP for the maximization of social rewards, without paying the conventionally-required huge computational cost. The fluids estimate the reward probabilities of the options for the exploitation of past knowledge, and generate random fluctuations for the exploration of new knowledge for which the utilization of the fluid-derived fluctuations is more advantageous than applying artificial fluctuations. The fluid-derived fluctuations, which require exponentially-many combinatorial efforts when they are emulated using conventional digital computers, would exhibit their maximal computational power when tackling classes of problems that are more complex than CBP. Extending the current configuration of the device would trigger further studies related to harnessing the huge computational power of natural phenomena to solve a wide variety of complex societal problems.

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“…Such a nonlocal correlation, in the sense that the state-filling induced at one dot immediately alters the dynamics of the entire system, has been shown to enhance the performance in solving the BP. 24 Note also that fluctuation is essential in order to realize an "exploration" ability; that is to say, the probability of the excitation going to a dot irradiated with control light is not perfectly zero if the state-filling does not perfectly inhibit the transition, as mentioned earlier.…”

Section: A Architecturementioning

confidence: 99%

Decision making based on optical excitation transfer via near-field interactions between quantum dots

Naruse

Nomura

Aono

et al. 2014

Journal of Applied Physics

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Optical near-field interactions between nanostructured matter, such as quantum dots, result in unidirectional optical excitation transfer when energy dissipation is induced.This results in versatile spatiotemporal dynamics of the optical excitation, which can be controlled by engineering the dissipation processes and exploited to realize intelligent capabilities such as solution searching and decision making. Here we experimentally demonstrate the ability to solve a decision making problem on the basis of optical excitation transfer via near-field interactions by using colloidal quantum dots of different sizes, formed on a geometry-controlled substrate. We characterize the energy transfer behavior due to multiple control light patterns and experimentally demonstrate the ability to solve the multi-armed bandit problem. Our work makes a decisive step towards the practical design of nanophotonic systems capable of efficient decision making, one of the most important intellectual attributes of the human brain.3

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Tug-of-war model for the two-bandit problem: Nonlocally-correlated parallel exploration via resource conservation

Cited by 79 publications

References 14 publications

A Model of Amoeba-Based Neurocomputer

A Model of Amoeba-Based Neurocomputer

Harnessing the Computational Power of Fluids for Optimization of Collective Decision Making

Decision making based on optical excitation transfer via near-field interactions between quantum dots

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