In this paper, we study the multicast capacity of a large scale random wireless network. We simply consider the extended multihop network, where a number of wireless nodes vi(1 ≤ i ≤ n) are randomly located in a square region with side-length a = √n, by use of Poisson distribution with density 1. All nodes transmit at constant power P, and the power decays along path, with attenuation exponent α > 2. The data rate of a transmission is determined by the SINR as B log(1 + SINR). There are ns randomly and independently chosen multicast sessions. Each multicast has k randomly chosen terminals. We show that, when k ≤ θ1 n/(log n)2α+6, and ns ≥ θ2n1/2+β, the capacity that each multicast session can achieve, with high probability, is at least c8√n/ns√k, where θ1, θ2, and c8 are some special constants and β > 0 is any positive real number. Our result generalizes the unicast capacity [3] for random networks using percolation theory.

A quasi-passive dynamic walking robot is built to study natural and energy-efficient biped walking. The robot is actuated by MACCEPA actuators. A reinforcement learning based control method is proposed to enhance the robustness and stability of the robot's walking. The proposed method first learns the desired gait for the robot's walking on a flat floor. Then a fuzzy advantage learning method is used to control it to walk on uneven floor. The effectiveness of the method is verified by simulation results.

We present a dynamic cognitive network (DCN) which is a systematic extension of the fuzzy cognitive map (FCM). Each concept in a dynamic cognitive network can have its own value set, depending on how precisely it needs to be described in the network. This enables the dynamic cognitive network to describe the strength of the cause and the degree of the effect. This ability also enables DCN to carry out inferences via numerical calculation instead of symbolic deduction. The arcs of DCN define dynamic relationships between concepts and describe the causal procedures. DCN overcomes the problems of FCM without losing the essential advantages.