Achieving autonomy - the ability and authority to act on one’s own volition - is generally a sign of maturity in humans. In machines, it means that some aspect(s) of control or decision-making has been ceded by humans. As we get comfortable with delegating routine domestic tasks to home robots and prepare for a world with self-driving cars and beyond, it is important to understand the opportunities and limits for autonomous systems. Asimov’s Three Laws of Robotics was a good start for programming behavioral constraints, but the world of tomorrow will need more. In this webinar participants will learn about the current state of autonomous systems development, and design constraints for the independent and collaborating autonomous solutions of the future.

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Autonomous Systems
from
Science Fiction to Commercial Solutions
Adrian Bowles, PhD
Founder, STORM Insights, Inc.
info@storminsights.com
Image Credit: Huffington Post Canada, 7/2/2013

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systems
Autonomy is about Control

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Robocop is cool, but…Roomba is Real

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(c)
From Humble Beginnings

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Autonomous: The ability to make one’s own decisions.
Automatic: A system that responds to environmental input with pre-programmed responses.
Semi-autonomous: A system capable of making [some] decisions based on
context, and relying on human intervention or override for others.
self-control
A single system may have multiple modes.

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9/7/2016

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BigDog is a dynamically stable
quadruped robot created in 2005 by
Boston Dynamics with Foster-Miller, the
NASA Jet Propulsion Laboratory, and the
Harvard University Concord Field Station.
[1] It was funded by DARPA, but the
project was shelved after the BigDog was
deemed too loud for combat.[2]
BigDog. (2016, August 19). In Wikipedia, The Free Encyclopedia. Retrieved 19:15, September 7, 2016, from https://en.wikipedia.org/w/index.php?title=BigDog&oldid=735286400
MQ-9 Reaper
Unmanned Areal Vehicle (UAV/Drone)
Sometimes, a little autonomy goes a long way.

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Sometimes
semi-autonomous
isn’t enough

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AutoSys
Decision-making…
Does it plan?
Generative planning?
Use feedback?
Coordinate?
Can it:
move?
in the air?
on land?
on/under water?
see?
hear?
smell?
taste?
feel?
learn?
Classifying Autonomous Systems

10. Autonomous
Systems
Copyright (c) 2016 by STORM Insights Inc. All Rights reserved.
Robots
Semi-Autonomous
Robot/automaton/android
Machine that performs one or more physical tasks
determined by preprogrammed instructions or
determined by autonomous reasoning.
Autonomous
Systems

11. Autonomous
Systems
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Consumer
Enterprise
Robots
Home
CleaningEldercare
Semi-Autonomous
Automobiles
Info
Retrieval
Robot/automaton/android
Machine that performs one or more physical tasks
determined by preprogrammed instructions or
determined by autonomous reasoning.
Autonomous
Systems

12. Autonomous
Systems
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Consumer
Public Sector Robots
Home
CleaningEldercare
Semi-Autonomous
UAVs
Automobiles
Buses
Trucks
Multi-
peds
Info
Retrieval
Robot/automaton/android
Machine that performs one or more physical tasks
determined by preprogrammed instructions or
determined by autonomous reasoning.
Autonomous
Systems

13. Autonomous
Systems
Copyright (c) 2016 by STORM Insights Inc. All Rights reserved.
Consumer
Public Sector
Enterprise
Robots
Home
CleaningEldercare
Manufacturing
Semi-Autonomous
UAVs
Automobiles
Buses
Trucks
Inventory Mgmt
Multi-
peds
Info
Retrieval
CognitiveCommerce
Apps
Robot/automaton/android
Machine that performs one or more physical tasks
determined by preprogrammed instructions or
determined by autonomous reasoning.
Network
Monitoring
Autonomous
Systems

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• A robot may not injure a human being or, through inaction,
allow a human being to come to harm.
• A robot must obey orders given it by human beings
except where such orders would conflict with the First Law.
• A robot must protect its own existence
as long as such protection does not conflict with the First or Second Law.
Isaac Asimov - Three Laws of Robotics
“Handbook of Robotics, 56th Edition, 2058AD”
in
Runaround, a 1942 short story

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Google Patents Emergency Vehicle
Detection for Autonomous Cars
9/6/2016

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Olli
Self-driving 12 passenger bus
Designed by Local Motors
With “passenger experience”
improved by IBM Watson
(speech to text, natural language
classifier, entity extraction,
text to speech, and
vehicle sensor analysis)
Olli
In tests now in DC

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9/7/2016
homeai.info

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OrientAct
Observe
Decide
World
Model
Formalizing the Decision Process
Boyd’s Loop
John Boyd (1927-1997)

21. Decisions Under Duress
Multiple sensors & Effectors

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OrientAct
Observe
Decide
Small
Model
Formalizing the
Control Process
OrientAct
Observe
Decide
Small
Model
feedback
Sensor
Sensor
Effector
Effector

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Copyright (c) 2014 by STORM Insights, Inc. All Rights Reserved.
Perception/
Language
Autonomic
Problem Solving
Reasoning & Learning
Simple:
deterministic,
retrieve/calculate
Complex:
probabalistic
hypothesize, test,
rank, select
Creative:
discover, generate
Memory
Stimulus/
Sensor
Response/
Effector
Input Class/Type
Visual
Text
Image
Aural
Speech
Music
Cues
Noise
Informative
Touch
Temperature
Tactile
Texture
Taste
Smell
Response Types
Visible (to the environment)
Verbal/NL Text
Behavioral (system changes)
Haptics/Touch/Proprioception
Invisible
Memory updates/
Feedback

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Key approaches to
reinforcement
Machine
Learning
unsupervised
supervised
The system is taught to detect or match patterns
based on training data. Learning by example.
The system learns/develops strategies based on
performance feedback.
An unsupervised learning system discovers patterns
based on experience.

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Control & Complexity
Low High
AutonomyAutomatic/Reflexive Autonomous
Independent InterdependentIntegration
World Model ComprehensiveNone

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Autonomous Systems Artificial General Intelligence
Machine
Learning
Cognitive ComputingThe Internet of Things
Understand
Reason
Respond
Learn
Domain-independent
problem solving
Connectivity
Control
Autonomous Systems in Context

27. Ethics
&
Issues
“I’m sorry Dave, I’m afraid I can’t do that…
This mission is too important for me to allow you to jeopardize it…
I know that you an Frank were planning to disconnect me
and I’m afraid that’s something I cannot allow to happen.”
HAL, 2001 A Space Odyssey

28. For more information:
Copyright (c) 2016 by STORM Insights Inc. All Rights reserved.
adrian@storminsights.com
Twitter @ajbowles
Skype ajbowles
Upcoming Webinar Dates & Topics
October 13 Deep QA (Question/Answer) - Lessons From Watson and Jeopardy!
November 10 Emerging Hardware Choices for Modern AI Data Management
December 8 Leverage the IOT to Build a Smart Data Ecosystem