In this paper, we propose new Metropolis–Hastings and simulated annealing algorithms on a finite state space via modifying the energy landscape. The core idea of landscape modification rests on introducing a parameter c, such that the landscape is modified once the algorithm is above this threshold parameter to encourage exploration, while the original landscape is utilized when the algorithm is below the threshold for exploitation purposes. We illustrate the power and benefits of landscape modification by investigating its effect on the classical Curie–Weiss model with Glauber dynamics and external magnetic field in the subcritical regime. This leads to a landscape-modified mean-field equation, and with appropriate choice of c the free energy landscape can be transformed from a double-well into a single-well landscape, while the location of the global minimum is preserved on the modified landscape. Consequently, running algorithms on the modified landscape can improve the convergence to the ground state in the Curie–Weiss model. In the setting of simulated annealing, we demonstrate that landscape modification can yield improved or even subexponential mean tunnelling time between global minima in the low-temperature regime by appropriate choice of c, and we give a convergence guarantee using an improved logarithmic cooling schedule with reduced critical height. We also discuss connections between landscape modification and other acceleration techniques, such as Catoni’s energy transformation algorithm, preconditioning, importance sampling, and quantum annealing. The technique developed in this paper is not limited to simulated annealing, but is broadly applicable to any difference-based discrete optimization algorithm by a change of landscape.

Organizational interactions in fields, including their antecedents and consequences, remain under-researched, in particular with regard to relational distance and transformative skills. Through a comparative study of the German and Japanese wind power sectors, we explore the importance of distance among organizational actors and the development of skills. While in the case of Germany a radical increase in wind energy generation can be witnessed, the situation in the field of Japanese wind power remains largely unchanged. We show how different degrees of distance among organizational actors in these two countries result in the different development of skills that stimulate transformation in the field of energy generation. More precisely, we illustrate the pivotal role of distant challengers with their transformative skills for the successful conversion of already established field structures. Our study contributes to field theory by elaborating on the understanding of the evolution of relational distance, thereby grasping the dynamic interplay between the diversity of actors and their skill formation within a certain strategic action field.

Passive walking robots can walk on a slight downward slope powered only by gravity. We propose a novel control strategy based on forced entrainment to stabilize a three-dimensional quasi-passive walking robot in uphill and level walking by using torso control in the frontal plane and synchronization of lateral motion with swing leg motion. We investigated the robot's walking energy efficiency, energy transformation, and transfer in simulation. The results showed that the proposed method is effective and energy-efficient for uphill and level walking. The relationship between energy utilization rate of actuation and energy efficiency of the robot was revealed, and mechanical energy transformation and transfer were characterized.