Analyses of chaos generated by neural-network-differential-equation for intelligent fish-catching
Takashi Tomono, Yuya Itou, Mamoru Minami, Akira Yanou · 2012
Continuous catching and releasing experiment of several fishes make the fishes find some escaping strategies. To make fish-catching robot intelligent more than fish's adapting and escaping abilities, we have proposed 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 since unpredictable chaotic motions of net may go beyond the fish's adapting abilities. In this report we examine interesting chaotic characters of plural chaos generated by NNDE through Lyapunov number, Poincare return map, initial value sensitivity and bifurcation map.