1. Agenda 12:00 – 1:00 PM Registration, Poster Setup, and Networking
  Welcome, Admin Announcements and Agenda Overview
  John Paschkewitz, DSO Program Manager 
1:05 – 1:10 PM
  Contract Management Office (CMO) Overview
  Michael Mutty, Contracting Officer
1:10 – 1:25 PM
  Defense Sciences Office (DSO) Overview
  Bill Regli, DSO Deputy Director
1:25 – 2:25 PM
  CASCADE Overview
2:25 – 2:45 PM 
  Government-Only Meeting
  (Review and answer question cards)
2:45 – 3:00 PM
  Question and Answer Session (Live and Webcasted)
3:00 – 5:00 PM
  Poster Session, Networking, and Sidebars
Distribution Statement “A” (Approved for Public Release, Distribution Unlimited)

2. Michael Mutty DARPA Contract Management Office
DARPA BAA PROCESS
Michael Mutty
DARPA Contract Management Office
December 9, 2015
Distribution Statement “A” (Approved for Public Release, Distribution Unlimited)

3. READ THE BAA BAA PROCESS DRAFTING THE BAA Technical vs Administrative
Words are Meaningful
Must and Shall
May
Technical vs Administrative
Technical Leads to “Selectable”
Administrative Leads to Contract Award
Cost Proposal
IP Assertions
Distribution Statement “A” (Approved for Public Release, Distribution Unlimited)

4. BAA PROCESS PROPOSAL PREPARATION/SUBMISSION
Instructions are detailed in the BAA (Follow closely)
ALL questions to program mailbox:
FAQ (including today’s) will be available on the program website on the DSO Homepage (Read Regularly)
Funding instrument types may vary from program to program but may include procurement contract(s), other transactions, assistance instruments (cooperative agreements)
Assert rights to all technical data & computer software generated, developed, and/or delivered to which the Government will receive less than Unlimited Rights
If you don’t justify your proposed costs, we can’t justify awarding you a contract.
Pay close attention to cost proposal instructions
Distribution Statement “A” (Approved for Public Release, Distribution Unlimited)

5. BAA PROCESS EVALUATION/AWARD
Read Evaluation Criteria Carefully
Government reserves the right to select for award all, some (partial selection), or none of the proposals received.
Government anticipates making multiple awards
No common Statement of Work - Proposals evaluated on individual merit and relevance as it relates to the stated research goals/objectives rather than against each other
Overview of the Process
3 Government Reviewers
PM Recommendation to the SRO
Notification
Distribution Statement “A” (Approved for Public Release, Distribution Unlimited)

6. Distribution Statement “A” (Approved for Public Release, Distribution Unlimited)

7. Defense Sciences Office
Dr. Bill Regli
December 9, 2015
Distribution Statement “A” (Approved for Public Release, Distribution Unlimited)

8. DARPA’s Mission: Breakthrough Technologies For National Security
Precision Guidance & Navigation
Communications/Networking
IR Night Vision
Stealth
UAVs
Investing today
for the next generation
1960s
1970s
1980s
1990s
2000s
2010s
2020s
2030s
Microelectronics: VLSI, CAD, manufacturing, IR, RF, MEMS
ARPAnet/Internet
Information Technology: timesharing, client/server, graphics, GUI, RISC, parallel computing, speech recognition
Materials Science: semiconductors, superalloys, carbon fibers, composites, thermoelectrics, ceramics
These new capabilities require a healthy ecosystem across Service S&T, universities, and industry
DARPA’s role: pivotal early investments that change what’s possible
Distribution Statement “A” (Approved for Public Release, Distribution Unlimited)

9. DARPA Technical Offices
BIOLOGICAL
TECHNOLOGY
OFFICE
DEFENSE SCIENCE
OFFICE
INFORMATION INNOVATION
OFFICE
MICROSYSTEMS
TECHNOLOGY
OFFICE
STRATEGIC TECHNOLOGY
OFFICE
TACTICAL TECHNOLOGY
OFFICE
Biological Complexity at Scale
Neurotechnologies
Engineering Biology
Restore, Maintain and Improve Warfighter Abilities
Math, Modeling & Design
Physical Systems
Human-Machine Systems
Empower the Human within the Information Ecosystem
Guarantee Trustworthy Computing and Information
Electromagnetic Spectrum
Tactical Information Extraction
Globalization
System of Systems (SoS)
Battle Management/Command and Control (BMC2)
Communications and Networks (C&N)
Electronic Warfare (EW)
Intelligence Surveillance, and Reconnaissance (ISR)
Positioning, Navigation, and Timing (PNT)
System Focus Areas:
Ground
Maritime
Air
Space
Crosscutting Themes:
Agile development
Cooperative Autonomy
Unmanned Systems
Power and Propulsion
Distribution Statement “A” (Approved for Public Release, Distribution Unlimited)

10. DSO is “DARPA’s DARPA”
Accelerating breakthrough discoveries to create new enabling technologies for national security
Distribution Statement “A” (Approved for Public Release, Distribution Unlimited)

11. Human-Machine Systems
Focus Areas
Math, Modeling&
Design
Physical Systems
© 2007 Ned Batchelder
Human-Machine Systems
Credit: Detroit Institute of Arts
Social Systems
The Economist, April 2012
Distribution Statement “A” (Approved for Public Release, Distribution Unlimited)

12. We look forward to your ideas
Distribution Statement “A” (Approved for Public Release, Distribution Unlimited)

13. Complex Adaptive System Composition And Design Environment (CASCADE)
Dr. John Paschkewitz
DSO
December 9, 2015
Distribution Statement "A" (Approved for Public Release, Distribution unlimited)

14. How can we design complex systems to meet unanticipated needs
How can we design complex systems to meet unanticipated needs? Using arbitrary components?
Structure: buildings, HVAC, power grid, water network, roads, vehicles, ...
Behaviors: electrical transmission, working sanitation, transportation…
Function
Constraints: road capacity, power grid capacity and storage, …
Events: blizzard, earthquake, tsunami with nuclear event…
Resilient urban infrastructure
healthcare, housing, public safety, sustenance, …
Christchurch, New Zealand, 2011
(Commons.Wikimedia.org)
Define a framework for thinking about systems
Resilient and adaptive means that we need to think about *dynamics* of composition, with changing pieces and BC’s.
Need: Fundamentally change how we design systems for real-time resilient response to dynamic, unexpected environments
Distribution Statement "A" (Approved for Public Release, Distribution unlimited)

15. Complex military systems can be similarly composed – and have similar challenges
Air Dominance SoS
Functions: strike, ISR, EW, …
Structures: manned and unmanned assets, communication networks, subsystems, materials, ….
Behaviors: communications, PNT, jamming, transportation, …
Constraints: power, logistics tail, …
Events: environmental challenges, attrition, surprise red team capability, …
Forward surgical capability
Functions: resuscitative surgery, medevac
Structures: surgeons, helicopters, communication networks,…
Behaviors: medical skills, transportation
Constraints: time, blood supply, mobility, surgeon risk, patient state…
Events: environmental challenges, communications jamming, …
The same framework can be used to think about military SoS. The system is complex because of the many scales of interaction and dynamics.
An example that has characteristics of both military and urban systems is a forward surgical team for battlefield medicine.
To help explain the program ideas, I’ll use this example because it highlights some aspects of complex systems design that are extremely challenging with today’s tools
An FST is 2 medics, 2 nurses and 2 surgeons with enough supplies to do 8 surgeries. The goal is to reduce KIA/DOW’s by getting to surgery faster – time is critical!
Unfortunately, they don’t work – there was no statistical evidence of reduction of DOW’s in Iraq/Afgh.
What if we wanted to design a autonomous telesurgery option? Or a fast, unmanned medevac system? How would we do the tradeoff analysis of the 2, which involves everything from surgical skills to logistics to engineering?
Complexity results from interactions between structures and behaviors across multiple time and spatial scales
Distribution Statement "A" (Approved for Public Release, Distribution unlimited)

16. Why can’t we design resource-efficient resilient and adaptive complex systems today?
Design cycle
Engineering models compose system structures and behavior
Logistics and time provide constraints
Empirical assessment of function
Mission models define events
Limitations & Challenges:
Composition of structures, behaviors and constraints across scales and time
Adaptation to dynamic environments with evolving threats in real time
The problem is hard because today’s tools can’t compose disparate structures and behaviors in a unified way. Adaptation amplifies these problems because we have a design cycle that is decoupled, slow and is built to anticipate a small number of events.
We can make a system resilient by giving it lots of redundancy in anticipation of known contingencies.
We can make it adaptive by training it for known threats.
What if we had a way to understand design interactions across all dimensions of structure and behavior at the same time?
To anticipate or even exploit interaction cascades? To enable a system to understand a full set of creative options to adapt?
Goal: Demonstrate a validated capability to model and design complex adaptive systems starting from new mathematical foundations for composition and adaptation
Distribution Statement "A" (Approved for Public Release, Distribution unlimited)

17. Program elements
Metrics
Computational complexity
Formal verifiability
Approximation methods
Compositional generality
Resilience and Adaptiveness limits
Challenge
Integrate formal mathematics for unified design
TA1: Foundations
Integrated teams address abstraction, composition and adaptation
Challenge
Build new design framework from mathematics up
TA2: Applications
Develop a new design capability for military SoS or urban resilience with TA1 teams
Metric
Prediction and design against real-world problems
Government Challenge Partner
Surprise problems and metrics
T&E partner
Single, collaborative test environment
End product: Complex adaptive system design tools with a library of resilient and adaptive designs
Distribution Statement "A" (Approved for Public Release, Distribution unlimited)

18. Program Schedule FY2016 FY2017 FY2018 FY2019 FY2020 Phase 1 Phase 2
12 mos.
Phase 2
Phase 3
Phase 4
Establish design foundations
Baseline Model (14 months)
Design Challenge 1: Basic Resilience (22 months)
Design Challenge 2: Adaptation
(34 months)
Design Challenge 3: Living Systems (46 months)
TA1: Foundations
New complex adaptive system design tools
Library of adaptive system architectures
Unified abstraction, composition and adaptation framework
“Pseudo-API” for TA2
Develop basic M&S infrastructure using TA1 foundations
Time-dependent Adaptive Composition (e.g. for pervasive sensing)
Dynamic and Resilient Functional composition
TA2: Applications
Define problems, demonstrate test “harness” and SOA performance
T&E environment
partner
Unified development and testbed environment
Split to ITAR (SoS) and non-ITAR (urban) environments
Government Challenge & IV&V partner
Establish appropriate level of detail, metrics for baseline with TA2’s
Define detailed surprise challenge 1 parameters and metrics
Define detailed surprise challenge 2 parameters and metrics
Define detailed surprise challenge 3 parameters and metrics
Distribution Statement "A" (Approved for Public Release, Distribution unlimited)

19. TA1: Mathematical Foundations
GOAL: provide a unified formal mathematical foundation for complex adaptive system design incorporating abstraction, composition and adaptation
Abstraction
Describe system structures, behaviors, constraints and events in a way that exposes only the information required to define the resulting function
Address the complexity of interfaces, multiscale interactions, and dynamics in a computable and computationally tractable manner
Want a uniform, formal approach across all scales and domains
Possible approaches: Category theory, Model theory
Composition
Enable general synthesis of functions from structures and behaviors, subject to constraints, in response to events – must include dynamics
Demonstrate both compositionality and composability
Possible approaches: algebraic geometry and topology, sheaf theory, cochain and process algebra
Adaptation
Enabled by a unified view (abstraction) and a formal language for composition of functions from arbitrary structures and behaviors
Requires assessment of environment and system state under uncertainty
Reason over system state to achieve functional “equivalence” using real-time composition
Must address stochasticity and reasoning over uncertainty in a principled manner
Images: top: middle: c/o Rob Ghrist, UPenn, bottom:
Distribution Statement "A" (Approved for Public Release, Distribution unlimited)

20. TA2: Applications
GOAL: Integrate deep knowledge of application area challenges and the new mathematical foundations of TA1 in powerful domain-specific modeling and design frameworks
Choose 1 of 2 application areas (see the BAA for more details):
Military systems of systems (SoS) at the unclassified level – e.g., adaptive battlefield medicine, logistics, maintenance
Resilient urban infrastructure – e.g., Dynamic community function (e.g. health care, public safety) requiring composition of power, water, logistics, architecture, etc.
TA2 Proposers must define:
System complexity – why can’t this be adequately modeled now?
Strategy for design framework – how will TA1 breakthroughs help and how will they be implemented?
System metrics – what are figures of merit for both design tools & systems being designed?
Transition strategy to application community – require open access to design capability and data
Must have integrated TA2 prime with TA1 subcontractor teams for phases 2-4
Distribution Statement "A" (Approved for Public Release, Distribution unlimited)

21. Example Challenge Problems: Urban Resilience
Quantitative metrics to be established for specific proposer focus by government challenge partner
Phase 2: Resilience
Predict community function in response to adverse event that does not permanently affect structure
Example: Blizzard
Identify most effective strategy for restoring community function to baseline state (determined at start of phase 2) and demonstrate a novel capability to design a more resilient architecture
Phase 3: Adaptation
Predict community function in response event that permanently destroys structures and changes behaviors & radically changes constraints
Example: Tornado, earthquake
Identify most effective strategy for restoring community function to baseline state and alternative designs that are more resilient
Phase 4: Living Systems
Predict community function in response to adverse event with co-evolving threat with unknown set of time-variable structures, behaviors and constraints
Example: Disease outbreak after natural disaster
Identify most effective strategy for restoring community function to baseline state and alternative designs that are more resilient
Include distributed architectures for computation, sensing and control
All images: wikipedia.org
Distribution Statement "A" (Approved for Public Release, Distribution unlimited)