1. RRD - Rapid Research
and Development
Fast methodology for
intelligent software design
Dr. Valery Tsourikov
Valery Tsourikov 2012 (c). All rights reserved

2.  RRD methodology was born after graduates of
AICreates training course started intelligent
software projects and realized that they had to learn
newest ideas in mathematics, econometrics and
predictive analytics in a very short period of time
Valery Tsourikov 2012 (c). All rights reserved

3.  Artificial Intelligence Systems are complex
by nature
 A.I. is a very broad area and evolves rapidly
 To design good A.I. software developers
must quickly learn a lot of new knowledge
Problem: how to design complex A.I.
software in a short period of time?
Valery Tsourikov 2012 (c). All rights reserved

4.  All four activities happen simultaneously:
Learn - Research -Teach -Develop
 Each team member is a researcher who can
program, saving time on prototyping phase
 Project has two phases: Research-by-Prototyping
and Development
Valery Tsourikov 2012 (c). All rights reserved

5.  Intelligent software architect describes the project
and divides new topics among team members
 At frequent status meetings, each person teaches others
on his topic and shows current prototypes
 Prototypes are coded in high level language, like R
 At this phase changes of project requirements are
allowed between meetings after prototypes reviews
 Phase 1 ends after the architect approves methods,
structures and algorithms to be used in the software
Valery Tsourikov 2012 (c). All rights reserved

6.  Phase 2. Team starts normal design process,
using SCRUM/sprints methodology, for example
 Changes of specifications are not allowed
between sprints during Phase 2
Valery Tsourikov 2012 (c). All rights reserved

7.  Fast new knowledge acquisition by the group
 Research prototype can be created quickly even
if team members are not domain experts
 Of course, Phase 1 is pretty intensive, but
people usually love learning new things in
friendly team environment
Valery Tsourikov 2012 (c). All rights reserved

8.  Development of A.I. system for dynamic optimization of multi-
spread portfolios for Predictive StatArb trading strategies
 Team of five: architect – Ph.D. in A.I., three developers: two
Ph.D. students, one – graduate student
 Phase 1 – three weeks. Team quickly learned and prototyped
ensemble-type portfolios with different predictive components.
Languages used: R, C#.
 Research-by-Prototyping helped choose the latest methods for
Predictive StatArb. Software will be coded in C++ to deliver
superb performance, including high-frequency version
Valery Tsourikov 2012 (c). All rights reserved

9.  Team met twice a week, plus daily reports on Skype
 Lessons learned:
 RRD methodology greatly accelerates development
of complex A.I. software
 R language is very good for prototyping
 Saturday meetings were the most productive,
because the team wasn’t disturbed
 Enthusiasm of team members is still the most
important factor of success
Valery Tsourikov 2012 (c). All rights reserved

10.  Rapid R&D methodology was designed to accelerate
development of complex intelligent software
 All team members must be able to do simultaneous
research and development
 RRD greatly reduces time-to-market cycle and helps
deliver software based on newest methods
Valery Tsourikov 2012 (c). All rights reserved