N12A-T013 TITLE: Computing With Chaos

TECHNOLOGY AREAS: Information Systems

OBJECTIVE: Utilize the concept of nonlinear dynamical chaos to create a chaos-based computer for a novel approach to information processing that has the potential to be superior to existing technologies in finding optimal solutions for problem solving and decision-making. This research includes developing the software to program this chaos-based computer.

DESCRIPTION: Nonlinear dynamics has revealed a rich array of behaviors, especially those related to chaos including routes to chaos, high and low dimensional chaotic attractors, crises, transient chaos, and Hamiltonian strange kinetics. In neural systems, measured phenomena includes chaos, synchrony, and cascading avalanches demonstrating that information processing in the brain is not just anatomical, but also dynamical. This program seeks to take advantage of the richness of nonlinear dynamical systems and insights from neural systems to devise new approaches to computation. Possible approaches include utilizing computing with attractors, transient chaos in high dimensional systems, chaos controlled reconfigurable logic gates, and pattern formation. Cues may be taken from neuroscience with network topologies of excitatory and inhibitory connections and plasticity of learning through strengthening of connections at synapses. We seek a "plastic" computational network that can be programmed to adjust rapidly without a physical rewiring to seek optimal solutions to problems. The sought after approach is to include nonlinear dynamical behaviors into an information processing system that can optimize solutions to complex problems. This research promises a revolution in information processing for areas such as pattern recognition where a complex circuit can self-organize by morphing between logic gate configurations to search for specific patterns, such as, faces, or vehicles. The incorporation of concepts from neural cognitive behavior can led to feedback and self-organization designs to increase the effectiveness of information processing. Novel computing can allow for a versatile response to information flow which can lead to new paradigms for the optimization of solving complex problems, such as the control of robots and other autonomous systems.

PHASE I: Design a computational system that is based on the nonlinear dynamical principles of chaos that can perform all logical operations. Provide a feedback mechanism that can allow the system to self-organize its logic to optimize solutions to tasks.

PHASE II: Further develop the computation system from Phase I to maximize its computational speed and minimize the number of logic gates and wiring connections to reduce cooling requirements. Build the computational system on a chip and demonstrate its ability to find optimal solutions to a complex task.

PHASE III: Build nonlinear dynamical computers with self-organizing logic to optimize solutions to tasks, such as, controllers for autonomous systems, including robots and vehicles. This includes developing a programming language for general computational problems.

PRIVATE SECTOR COMMERCIAL POTENTIAL/DUAL-USE APPLICATIONS: A reconfigurable chaos-based computer will be of value to military and civilian customers. Reuse of logic gates whose logic is morphable can led to the need for fewer logic gates. This will decrease wiring requirements and lower heat production. This alone will be a strong positive factor for industry as it will lower cooling requirements. The chaos-based computer will offer new approaches to problems in pattern recognition, voice recognition, and controller for autonomous vehicles and robotic platforms.

REFERENCES:
1. T. M. McKenna et. al., The Brain as a Dynamic Physical System, Neuroscience 60, 587-605 (1994).

2. W. L. Ditto et. al."Chaos Computing: Ideas and Implementations", Phil. Trans. Roy. Soc. A366 653 (2008).

3. M. I. Rabinovich et. al., "Transient Cognitive Dynamics, Metastability and Decision Making", PLoS Comput. Biol. 24 1000072 (2008)

4. I. Tsuda, "Hypotheses on the Functional Roles of Chaotic Transient Dynamics", Chaos 19 015113 (2009).

5. D. Plenz and T. C. Thiagarajan, "The Organizing Principles of Neuronal Avalanches: Cell Assembles in the Cortex", Trends in Neuroscience 30 101 (2007).

KEYWORDS: chaos; nonlinear dynamics; computation; logic gates; reconfigurable; self-organization

Questions may also be submitted through DoD SBIR/STTR SITIS website.