Inspired by the efficient method of locomotion of the rattlesnake Crotalus cerastes, the objective of this work is automatic design through genetic programming (GP) of the fastest possible (sidewinding) locomotion of simulated limbless, wheelless snake-like robot (Snakebot). The realism of simulation is ensured by employing the Open Dynamics Engine (ODE), which facilitates implementation of all physical forces, resulting from the actuators, joints constrains, frictions, gravity, and collisions. Reduction of the search space of the GP is achieved by representation of Snakebot as a system comprising identical morphological segments and by automatic definition of code fragments, shared among (and expressing the correlation between) the evolved dynamics of the vertical and horizontal turning angles of the actuators of Snakebot. Empirically obtained results demonstrate the emergence of sidewinding locomotion from relatively simple motion patterns of morphological segments. Robustness of the sidewinding Snakebot, which is considered to be the ability to retain its velocity when situated in an unanticipated environment, is illustrated by the ease with which Snakebot overcomes various types of obstacles such as a pile of or burial under boxes, rugged terrain, and small walls. The ability of Snakebot to adapt to partial damage by gradually improving its velocity characteristics is discussed. Discovering compensatory locomotion traits, Snakebot recovers completely from single damage and recovers a major extent of its original velocity when more significant damage is inflicted. Exploring the opportunity for automatic design and adaptation of a simulated artifact, this work could be considered as a step toward building real Snakebots, which are able to perform robustly in difficult environments.

The objective of this work is automatic design through genetic programming, of the fastest possible locomotion of simulated snake-like robot (Snakebot). The realism of simulation is ensured by employing the Open Dynamics Engine software library. Empirical results demonstrate the emergence of sidewinding as fastest locomotion gait. Robustness of the sidewinding is illustrated by the ease with which Snakebot overcomes various types of obstacles. The ability of Snakebot to adapt to partial damage by gradually improving its velocity characteristics is shown. Discovering compensatory locomotion traits, Snakebot recovers completely from single damage and recovers a major extent of its original velocity when more significant damage is inflicted.

Presents the results of some of the first evolvability experiments undertaken on CAM (content-addressable memory) brain machines (CBMs), using the hardware itself (not software simulations). A CBM is a specialised piece of programmable (evolvable) hardware that uses Xilinx XC6264 programmable FPGA chips to grow and evolve, at electronic speeds, 3D cellular automata (CA) based neural network circuit modules of some 1,000 neurons each. A complete run of a genetic algorithm (e.g. with 100 generations and a population size of 100) is executed in a few seconds. 64,000 of these modules can be evolved separately according to the fitness definitions of human evolutionary engineers and downloaded, one by one, into a gigabyte of RAM. Human brain architects then interconnect these modules "by hand" according to their artificial brain architectures. The CBM then updates the binary neural signaling of the artificial brain (with 64,000 "hand" interconnected modules, i.e. 75 million neurons) at a rate of 130 billion CA cell updates a second, which is fast enough for the real-time control of robots. Before such multi-module artificial brains can be constructed, it is essential that the quality of the evolution (the "evolvability") of the individual modules should be adequate. This paper reports on the initial evolvability results obtained on CBM hardware.

Reversible logic is of increasing importance to many future computer technologies. We introduce a regular structure to realize symmetric functions in binary reversible logic. This structure, called a 2*2 net structure, allows for a more efficient realization of symmetric functions than the methods introduced by the other authors. Our synthesis method allows us to realize arbitrary symmetric function in a completely regular structure of reversible gates with relatively little "garbage". Because every Boolean function can be made symmetric by repeating input variables, our method is applicable to arbitrary multi-input multi-output Boolean functions and realizes such arbitrary function in a circuit with a relatively small number of additional gate outputs. The method can also be used in classical logic. Its advantages in terms of numbers of gates and inputs/outputs are especially seen for symmetric or incompletely specified functions with many outputs.