TT_Vol3 Issue2 - Raytheon

raytheon

TT_Vol3 Issue2 - Raytheon

Cognitive Computing

A Renaissance in Information Processing Technology

That’s how the Defense Advanced

Research Projects Agency (DARPA)

Information Processing Technology Office

(IPTO) views Cognitive Computing. A cognitive

system knows what it is doing. It can

reason, learn from experience, explain its

actions to the user, be told by the user

what to do, be self-aware and reflect on its

own behavior. Developing the computing

technology that will enable cognitive systems

with such attributes is the focus of

the recently recreated DARPA IPTO office.

Why do we need to impart such humanlike

capabilities to computers? The motivation

is not hard to find. Computer systems

are the backbone of many mission-critical

DoD systems. Looking more broadly,

computing and networking are becoming

pervasive in all aspects of society and the

national infrastructure is critically dependent

on their correct operation. Yet, while

realization of Moore’s law has resulted in

amazing growth in hardware capabilities,

thereby enabling exponentially growing

performance and functionality at ever

decreasing cost, many of the non-functional

properties of information systems have not

kept up. In fact, trustworthiness, productivity,

and effectiveness have all suffered. Systems

have grown more rigid and fragile. They

cannot gracefully change and adapt as user

requirements evolve or when unforeseen

operational conditions are encountered.

Cognitive computing is seen as the revolutionary

technology that will provide the required

quantum leap in non-functional properties.

Figure 1 depicts a strawman architecture

for providing cognitive capabilities. The

main elements of a cognitive system

include perception, communication, reasoning,

learning, and action. Systems today are

designed to be primarily reactive in nature.

They process inputs provided by sensors,

execute various preprogrammed algorithms

and computations and produce outputs

that then affect the external environment.

This is analogous to the lowest level of

human cognition, generally categorized as

a reflexive process. The next higher level of

cognition is a deliberative process. It

involves a degree of prediction

and planning, and

some reasoning. IBM’s

Deep Blue computer,

which defeated the world

chess champion, Gary

Kasparov, can certainly be

thought of as possessing

these attributes.

STM

The highest level of human

Attention

cognition is embodied in a

reflective process. It involves reasoning and

learning. A human can go back over a past

event and reflect on it. One can ask and try

to answer questions such as: What did I do

wrong? What did I do right? How should I

react the next time I’m faced with the same

situation? We generally call this learning from

experience. And since no situation repeats

exactly, we can also reason about what

lessons to apply to the current situation.

Of course, humans can also be taught,

and don’t learn only by making mistakes.

Supervised learning in information

systems is already considered a reasonably

successful story, at least in some

limited application domains. The truly

ambitious DARPA goal is to make breakthroughs

in reasoning and reinforcement

learning in varied environments. This is a

personal favorite of the DARPA Director,

Dr. Tony Tether.

The IPTO research thrusts, illustrated in

Figure 2, parallel various components of

the cognitive agent architecture.

Additionally, there is a line of research to

make the underlying hardware and software

of cognitive systems more robust,

ensuring they are impervious to their own

faults and resilient to external attacks. The

Self-Regenerative Systems program falls in

this class. (More details on the specific

research challenges in each of these areas,

as DARPA sees it, can be found on their

web site: http://www.darpa.mil/ipto)

Is any of this relevant to Raytheon’s business?

If so, how? Raytheon IDS has adopted

a new business model, which will be the

Refletive Processes

Deliberative Processes

Communication

(language,

gesture,

image)

Other

reasoning

Prediction/

planning

Perception Action

Sensors

Reactive Processes

Emotion

Effectors

External Environment

Figure 1. Strawman Architecture of a Cognitive Agent

leading Mission Systems Integrator for the

DoD. It requires core engineering competencies

in large-scale software and system

architecture development, integration, and

validation. As indicated above, the complexities

of such systems have grown along

with their functionality, resulting in a high

degree of fragility and inflexibility. And it is

well recognized that a major fraction of the

Cognitive

Teams

Knowledge

Representation

& Reasoning

Systems that Know

What They’re Doing

Cognitive Architecture

Learning

&

Perception

LTM

(knowledge based)

Concepts

Sentences

Systems

Communication

&

Interaction

Robust Software & Hardware

Infrastructure

Figure 2. Research Thrusts for Cognitive Computing

Applications

Core

Cognition

total development cost is incurred in the

integration and validation phases. The technologies

underlying cognitive systems have

the potential to reduce both these costs

and the high risks attendant in systems

integration. They can enable systems that

not only meet their performance and functional

requirements, but are also flexible,

adaptive, and robust to changing environmental

conditions and faults and attacks,

resulting in high mission assurance-a quality

in demand by both of our customers in

the DoD. �

7

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