https://www.selleckchem.com/products/gcn2-in-1.html In this study, we discovered a phenomenon in which a quadruped robot without any sensors or microprocessor can autonomously generate the various gait patterns of animals using actuator characteristics and select the gaits according to the speed. The robot has one DC motor on each limb and a slider-crank mechanism connected to the motor shaft. Since each motor is directly connected to a power supply, the robot only moves its foot on an elliptical trajectory under a constant voltage. Although this robot does not have any computational equipment such as sensors or microprocessors, when we applied a voltage to the motor, each limb begins to adjust its gait autonomously and finally converged to a steady gait pattern. Furthermore, by raising the input voltage from the power supply, the gait changed from a pace to a half-bound, according to the speed, and also we observed various gait patterns, such as a bound or a rotary gallop. We investigated the convergence property of the gaits for several initial states and input voltages and have described detailed experimental results of each gait observed.Due to the decentralized, loosely coupled nature of a swarm and to the lack of a general design methodology, the development of control software for robot swarms is typically an iterative process. Control software is generally modified and refined repeatedly, either manually or automatically, until satisfactory results are obtained. In this paper, we propose a technique based on off-policy evaluation to estimate how the performance of an instance of control software-implemented as a probabilistic finite-state machine-would be impacted by modifying the structure and the value of the parameters. The proposed technique is particularly appealing when coupled with automatic design methods belonging to the AutoMoDe family, as it can exploit the data generated during the design process. The technique can be used either to reduce the co