With a few months delay, here
is my three-year research agenda for 2013-2015. I have found over the years
that this agenda helps me focus and avoid being distracted by too many
opportunities, since my free time has shrunk a lot now that I am responsible for
new (fixed-telecom) products. To make the best use of the few free week-ends
and vacation days, it works best to have a clear agenda with a few challenges.
me start with a short feedback on the previous plan. The first
topic was “Business communication model (BPCM) and Organizational
architecture”. I have made good progress on BPEM & BPCM and managed to
publish a paper at ICORES 2012. I have also
made some progress on modeling lean management as BPO (Business Process Optimization),
following Reinertsen’s tracks, but a
lot remains to be done. I have made no progress on SIFOA v2, this becomes a
goal for 2014.
have published a paper on GTES at CSDM 2012 and applied
GTES to Smart-Grid simulation, with success (cf. my ROADEF presentation). Still most of my research agenda on equilibriums stays for 2013-2015 (see later).
the other hand, I have not done much on my last theme “Information Theory and
Autonomous Systems”. I have dropped my lecture at Polytechnique, and new
interests (lean software factories, agile methods and architecture)
have displaced my previous plans regarding information systems architecture.
new research plan is organized into three parts as usual and is clearly geared
towards my next book which I intend to write in 2015, entitled “Enterprises
against complexity: from forecasting to games”. I conclude from the previous
retrospective that I should push a lighted agenda with fewer objectives :)
Game Theory and Market Equilibriums
key application of GTES has been to market equilibriums (equilibria for purists). Most of the work in the past 5 years has been
with CGS (Cellular Game Simulation), a GTES model which represents the
competition between phone operators. The major presentation at
INRIA in 2010 was dedicated to this topic. My further work on
modeling the introduction of Free into the market (cf. CSDM presentation) was
based on an even simpler representation of market competition. My goal for the next
two years is to deepen my analysis of “market equilibriums”:
- GTES versus classical equilibriums such as
I want to calibrate the results obtained through GTES simulation against the
classical equilibrium from game theory applied to economy (including Bertrand, Stackelberg
and others). The goal is two-folds: increase the credibility of GTES by
reproducing results from analytical methods with simple market equations, and
enrich our set of working market model with insights from economy theory.
- Repeated Tenders Market Shares.
This is a new project of mine for 2013, based on a discussion with Benoit Rottembourg.
The goal is to characterize equilibrium in a closed B2B market, such as
repeated tenders. One may think of an IS division which is issuing a number of
tenders for software development projects to the same set of ISV. Although a
crude reasoning might make one think that the stronger player will take all,
game theory shows that there is need to avoid monopoly which creates a more
diverse situation (as one may observe in real life).
- Bids, such as LTE bids in 2011.
GTES was applied at the end of 2011 to help simulate a few bidding strategies
when an auction was proposed by
for LTE frequencies. The complexity of the auction, with rules that govern the
bundles of frequencies allocated to bidding operators, translates into an
interesting game (although it is a “one-shot” auction, with a unique bid).
GTES : Towards a more robust framework
has proven quite successful over the past 10 years. The next step for the
coming years is to turn GTES into a robust framework, so that new problems and
models may be tackled with less effort and still more meaningful results. What follows is a quick overview of my goals
for the next three years, most of which have been around for a while:
- Include insights from relevant Game Theory
GTES is by no mean an original idea, it
borrows from Game Theory, Evolutionary game theory, Multi-Agent Systems, Discrete Choice Models, Stochastic Games and Markovian Decision Processes.
One of my goals is to better relate GTES with its siblings and borrow from existing
literature techniques to improve the stability (% of Monte-Carlo sampling that
yield and equilibrium) and the convergence rate (finding this equilibrium
faster). Stochastic Games (in the form of dynamic games with complete
information) have shown how to incorporate learning techniques (such as Q-learning or linear reward-inaction) to converge
faster towards Nash equilibriums than a simple “best response” fixed-point
iterative search. I have received a lot of help from my friends at ROADEF and I
am now looking at domains such as Multi-armed Bandit or online machine learning to find
inspiration. I found a reference to mixing Q-learning to PHC (Policy Hill Climbing) which is very
relevant to GTES
- Develop better satisfaction model and
This follows an insight gained with the S3G experiments, as well as the CGS
experiments. I have used a linear satisfaction formulation which would be
better replaced by a product formulation (classical insight from performance
management theory). I also want to develop a set of “generic local
optimization” heuristics, instead of re-writing ad hoc algorithm for each GTES
instantiation (mostly a combination of dichotomist local optimization and
- Propose a cloud distributed version using
a MapReduce architecture.
GTES may be one of the easiest possible algorithm to run in parallel (citer
CSDM), if only because Monte-Carlo sampling is trivial to distribute. My goal
is to develop a new release of CLAIRE (CLAIRE 3.4) that may run on cloud
infrastructure such as Amazon ECS (lien).
Lean Enterprise 2.0 Model (follow-up of SIFOA : Simulation of
Information Flows and Organizational Architecture)
last part of my three-year-plan is a follow-up of the SIFOA work which started
in 2006 and has been the main topic of my blog. I am now ready to return to
modeling and computational simulation, leveraging the work made both on:
- BPEM : a model of enterprise
value creation (cf. the previously mentioned ICORES article). One could
summarize my original intent in 2005 with the equation “SIFOA = dBPEM / dORG”,
that is, what is the structural effect of organizational architecture on
efficiency, as explained with a formal computational model.
- BPCM : a model that characterizes communication channels through their
throughput, latency and fidelity (opposite of loss). Most of my work on social
networks and affiliation networks has helped me define a simpler
model than what I was using seven years ago.
The key insight which I want to validate (or refute !)
with SIFOA is that managing communication is mostly managing a scarce time
resource which is made even rarer because of the increase of complexity (hence
of communication flows) and change frequency (hence work load). The goal of this second edition of SIFOA is
to provide with a computational model for Lean Enterprise 2.0 to book. This third topic contains the following:
- Better and simpler BPEM & BPCM models.
There are two specific goals related to my previous work: include social network &
other related work + better understanding of 2.0 channels. Still the main goal is to produce a simpler model, hence to lose some detail.
- Formal evidence of lean-style pull
management in an uncertain world.
Although lean is so much more than “good plumbing”, I have been surprised by
the strong demonstration of lean principles with the OAI simulation.
This simulation was based on application integration through business process
in information systems. I would like to reproduce similar results in the world
of business process efficiency, following the tracks of Reinertsen. Part of it
is well-known (application of queueing theory);
parts of it is more subtle (Jackson networks of
with irregular service laws) and part of it remains to be studied (importance
of control & information flows w.r.t. business process efficiency)
- Showcasing the necessity of 2.0
Another key intuition of my previous book
is that large-scale companies or divisions are faced with information flows of
such magnitude that they escape conventional tools and practices (they lead to
the syndrome “I am always in a meeting or answering my email”). SIFOA v2 aims
at running computing experiment which will demonstrate the scalability of new
forms of communication.