Multiple chaos generator by Neural-Network-Differential-Equation for intelligent fish-catching

Abstract

Continuous catching and releasing experiment of several fishes makes the fishes find some escaping strategies such as staying stationary at corner of the pool. To make fish-catching robot intelligent more than fishes' adapting and escaping abilities from chasing net attached at robot's hand, we thought something that goes beyond the fishes' adapting intelligence will be required. Here we propose a chaos-generator comprising Neural-Network-Differential-Equation(NNDE) and an evolving mechanism to have the NNDE generate chaotic trajectories as many as possible. We believe that the fish could not be adaptive enough to escape from chasing net with chaos motions that have many different chaos, since unpredictable chaotic motions of net may go beyond the fishes' adapting abilities to the net motions. In this report we introduce the chaos generating system by NNDE, which can produce many kinds of chaos theoretically, and then analyze the chaos with Lyapunov number, Poincare return map and initial value sensitivity.