Part of HRL's Information and Systems Sciences Laboratory, the Center for Neural and Emergent Systems (CNES) is dedicated to exploring and developing an innovative neural & emergent computing paradigm for creating intelligent, efficient machines that can interact with, react and adapt to, evolve, and learn from their environments.

CNES was founded on the principle that all intelligent systems are open thermodynamic systems capable of self-organization, whereby structural order emerges from disorder as a natural consequence of exchanging energy, matter or entropy with their environments.

These systems exist in a state far from equilibrium where the evolution of complex behaviors cannot be readily predicted from purely local interactions between the system's parts. Rather, the emergent order and structure of the system arises from manifold interactions of its parts. These emergent systems contain amplifying-damping loops as a result of which very small perturbations can cause large effects or no effect at all. They become adaptive when the component relationships within the system become tuned for a particular set of tasks.

CNES promotes the idea that the neural system in the brain is an example of such a complex adaptive system. A key goal of CNES is to explain how computations in the brain can help explain the realization of complex behaviors such as perception, planning, decision making and navigation due to brain-body-environment interactions.

We seek to apply the thermodynamic basis of self-organization to study a broader class of problems via physical manifestations of intelligence that may one day explain the emergence of behaviors in a wide range of complex physical systems—from animate systems, financial networks, social networks and other very large-scale complex systems.

CNES will exploit this understanding to engineer prototype intelligent systems for real-world applications, such as Intelligent surveillance and reconnaissance, unmanned autonomous systems, robotics for manufacturing and urban combat-and-rescue missions, autonomous driving and other applications.



02/2015 - CNES Director presents at the ITRS Workshop on Emerging Research Device Meeting held in Stanford University on February 26, 2015

12/2014 - Unsupervised Discrimination of Patterns In Spiking Neural Networks With Excitatory and Inhibitory Synaptic Plasticity

11/2014 - Prototype AI chip allows UAV to learn

11/2014 - A Brain-Inspired Chip Takes to the Sky

10/2014 - CNES Director participates in invited panel discussion on "Brains and Robots" at the RoboBusiness 2014 conference

10/2014 - Minds of Their Own

09/2014 - How IBM Got Brainlike Efficiency From the TrueNorth Chip

09/2014 - CNES Hosted the 3rd International Workshop on "The Brain: Criticality, Dynamics, Network and Function"

08/2014 - Microprocessors modeled on networks of nerve cells promise blazing speed at incredibly low power—if they live up to hopes

07/2014 - CNES Director gives plenary talk on "Thermodynamics and Intelligent Systems" at the Cellular Nanoscale Networks and their Applications (CNNA) conference

06/2014 - Neuromorphic Computing Gets Ready for the (Really) Big Time

04/2014 - Neuromorphic Chips

01/2014 - Processors That Work Like Brains Will Accelerate Artificial Intelligence

08/2013 - The Machine of A New Soul

06/2013 - HRL's RAPID UPSIDE team is awarded contract to develop new real-time tracking technology for DARPA

11/2012 - Researchers Receive Best Paper Award at ICDL-EpiRob 2012

03/2012 - Artificial synapses could lead to advanced computer memory and machines that mimic biological brains