1,275 research outputs found
Dynamic contests
Considering several main types of dynamic contests (the race, the tug-of-war, elimination contests and iterated incumbency fights) we identify a common pattern: the discouragement effect. This effect explains why the sum of rentseeking efforts often falls considerably short of the prize that is at stake. It may cause violent conflict in early rounds, but may also lead to long periods of peaceful interaction. -- Unter Berücksichtigung verschiedener Haupttypen dynamischer Wettbewerbe (das Wettrennen, das Tauziehen, Ausscheidungskämpfe und wiederholte Kämpfe um Amtszeiten) identifizieren die Autoren ein gemeinsames Muster: den Entmutigungseffekt. Dieser Effekt erklärt, wieso die Rent-seeking-Bemühungen in Summe oft deutlich nicht an den auf dem Spiel stehenden Preis heranreichen. Der Effekt kann heftige Kämpfe in den ersten Runden des Wettbewerbs auslösen, aber auch zu langen Perioden friedlichen Zusammenspiels führen.
Solving multi-armed bandit problems using a chaotic microresonator comb
The Multi-Armed Bandit (MAB) problem, foundational to reinforcement
learning-based decision-making, addresses the challenge of maximizing rewards
amidst multiple uncertain choices. While algorithmic solutions are effective,
their computational efficiency diminishes with increasing problem complexity.
Photonic accelerators, leveraging temporal and spatial-temporal chaos, have
emerged as promising alternatives. However, despite these advancements, current
approaches either compromise computation speed or amplify system complexity. In
this paper, we introduce a chaotic microresonator frequency comb (chaos comb)
to tackle the MAB problem, where each comb mode is assigned to a slot machine.
Through a proof-of-concept experiment, we employ 44 comb modes to address an
MAB with 44 slot machines, demonstrating performance competitive with both
conventional software algorithms and other photonic methods. Further, the
scalability of decision making is explored with up to 512 slot machines using
experimentally obtained temporal chaos in different time slots. Power-law
scalability is achieved with an exponent of 0.96, outperforming conventional
software-based algorithms. Moreover, we find that a numerically calculated
chaos comb accurately reproduces experimental results, paving the way for
discussions on strategies to increase the number of slot machines
The market for protection and the origin of the state
We examine a stark setting in which security or protection can be provided by self-governing groups or by for-profit entrepreneurs (kings, kleptocrats, or mafia dons). Though selfgovernance is best for the population, it faces problems of long-term viability. Typically, in providing security the equilibrium market structure involves competing lords, a condition that leads to a tragedy of coercion: all the savings from the provision of collective protection are dissipated and welfare can be as low as, or even lower than, in the absence of the state
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