Spatio-temporal patterns act as computational mechanisms governing emergent behavior in robotic swarms

Our goal is to control a robotic swarm without removing its swarm-like nature. In other words, we aim to intrinsically control a robotic swarm emergent behavior. Past attempts at governing robotic swarms or their self-coordinating emergent behavior, has proven ineffective, largely due to the swarm's inherent randomness (making it difficult to predict) and utter simplicity (they lack a leader, any kind of centralized control, long-range communication, global knowledge, complex internal models and only operate on a couple of basic, reactive rules). The main problem is that emergent phenomena itself is not fully understood, despite being at the forefront of current research. Research into 1D and 2D Cellular Automata has uncovered a hidden computational layer which bridges the micro-macro gap (i.e., how individual behaviors at the micro-level influence the global behaviors on the macro-level). We hypothesize that there also lie embedded computational mechanisms at the heart of a robotic swarm's emergent behavior. To test this theory, we proceeded to simulate robotic swarms (represented as both particles and dynamic networks) and then designed local rules to induce various types of intelligent, emergent behaviors (as well as designing genetic algorithms to evolve robotic swarms with emergent behaviors). Finally, we analysed these robotic swarms and successfully confirmed our hypothesis; analyzing their developments and interactions over time revealed various forms of embedded spatiotemporal patterns which store, propagate and parallel process information across the swarm according to some internal, collision-based logic (solving the mystery of how simple robots are able to self-coordinate and allow global behaviors to emerge across the swarm)

Differential effects of 670 and 830 nm red near infrared irradiation therapy: A comparative study of optic nerve injury, retinal degeneration, traumatic brain and spinal cord injury

Red/near-infrared irradiation therapy (R/NIR-IT) delivered by laser or light-emitting diode (LED) has improved functional outcomes in a range of CNS injuries. However, translation of R/NIR-IT to the clinic for treatment of neurotrauma has been hampered by lack of comparative information regarding the degree of penetration of the delivered irradiation to the injury site and the optimal treatment parameters for different CNS injuries. We compared the treatment efficacy of R/NIR-IT at 670 nm and 830 nm, provided by narrow-band LED arrays adjusted to produce equal irradiance, in four in vivo rat models of CNS injury: partial optic nerve transection, light-induced retinal degeneration, traumatic brain injury (TBI) and spinal cord injury (SCI). The number of photons of 670 nm or 830 nm light reaching the SCI injury site was 6.6% and 11.3% of emitted light respectively. Treatment of rats with 670 nm R/NIR-IT following partial optic nerve transection significantly increased the number of visual responses at 7 days after injury (P=0.05); 830 nm R/NIR-IT was partially effective. 670 nm R/NIR-IT also significantly reduced reactive species and both 670 nm and 830 nm R/NIR-IT reduced hydroxynonenal immunoreactivity (P=0.05) in this model. Pre-treatment of light-induced retinal degeneration with 670 nm R/NIR-IT significantly reduced the number of Tunel+ cells and 8-hydroxyguanosine immunoreactivity (P=0.05); outcomes in 830 nm R/NIR-IT treated animals were not significantly different to controls. Treatment of fluid-percussion TBI with 670 nm or 830 nm R/NIR-IT did not result in improvements in motor or sensory function or lesion size at 7 days (P > 0.05). Similarly, treatment of contusive SCI with 670 nm or 830 nm R/NIR-IT did not result in significant improvements in functional recovery or reduced cyst size at 28 days (P > 0.05). Outcomes from this comparative study indicate that it will be necessary to optimise delivery devices, wavelength, intensity and duration of R/NIR-IT individually for different CNS injury types