[eas_cs_seminars] 24th April 2018

[Luca Rossi]

Hi all,

Next Tuesday (24/04) Dr. Kirstie L. Bellman (Topcy House Consulting) will
give a talk titled "Extending Our Concepts of Self-Optimization and
Self-Improvement: From Tasks to Situations" in MB246A from 2pm to 3pm.

See below for a short bio and the abstract of the talk.

Best,
Luca

Abstract:
Current self-optimization generally makes the assumption that the system
has been given a set of goals, operating constraints, and requirements;
then the system continuously adjusts its repertoire of methods to adapt to
the current operational conditions in order to fulfill those requirements
and, even better, to improve on its performance for those requirements.
This is an important approach that has borne much fruit!

However, it also can lead to a singularly reactive and non-future thinking
system – a system driven by the current job at hand and one where the
system never gets out ahead of current conditions.
Consider some of the characteristics of natural systems: Animals are
willing to sacrifice current goals for better benefits later (even
extending into altruism at the societal level.) This type of optimization
includes what is needed for a better next move or better positioning (e.g.,
taking higher ground, building a burrow, retreating and running away to
survive long enough to regroup, letting the ball go past one so one can
protect the goalie, etc.) Animals also demonstrate merging of goals (which
can even mean underperforming on all current goals to some extent in order
to fulfill several goals in the current operational situation.) Animals
also have reasoning processes that reflect on past experience in order to
discover root causes of changes in the operating conditions or environment
or the system itself. They also learn to develop better automated responses
and ‘train’ (play) to systematize future reactions and to discover how best
to use their individual capabilities in a given environment. As part of
that, they invest in exploratory behavior in order to have better future
knowledge of the environment and potential applicable behaviors.  All of
these and many more behaviors and cognitive capabilities are examples of
stepping back from the immediate accomplishment of a goal or a performance
of an action in order to improve the system’s overall situation. We are
using the term “situation” in the technical sense, as defined by both the
Cognitive Simulation community and the self-awareness community, where
situation includes at least the elements of the situation, e.g., objects,
events, people, systems, environmental factors; their current states, e.g.,
locations, conditions, modes, and actions, and the system’s context
information and goals.

In this talk, we focus on a subset of the adaptive capabilities noted
above, giving examples of the abilities of animal systems to satisfy
multiple goals by combining behaviors, to forego obtainable immediate goals
in order to better position themselves for improved future behaviors and to
even alter their environments in order to improve the likelihood of
successful goal outcomes and their overall situation. We will then examine
the implications of each of the above for how we might want to better use
our current self-optimization methods and approaches and where we might
want to add additional capabilities to our repertoire of methods.  This
will include some examples of using different timescales in our
self-optimization approaches and having them operate in parallel, as well
as introducing multiple goals into our self-improvement processes. We will
also discuss what is needed to reason about better ‘future positioning.

Bio:
Dr. Kirstie Bellman has over thirty-five years of academic, industrial, and
consulting experience in both laboratory research and the development of
models and information architectures for large military and government
programs. Her published research spans a wide range of topics in Cognitive
Science, Neuroscience, and Computer Science. In addition to playing a
leading role in the development of programs in the error analysis and the
evaluation of Artificial Intelligence programs, her group did
internationally recognized research in conceptual design environments,
software integration, and architectures. She started the VEHICLES project,
an environment for the conceptual design of space systems that incorporates
both conventional and artificial intelligence methods. With Dr. Landauer,
she started the Wrappings approach to system integration and reflective
architectures that use models to manage their own resources and to reason
about appropriate behavior. Upon completion of her term at DARPA as a
Program Manager for the Domain-Specific Software Architectures program,
Prototech (rapid prototyping technology and mathematically-based
specification languages), Formal Foundations, and the large Computer-Aided
Education and Training Initiative, she received an award from the U.S.
Secretary of Defense for excellence in her programs. While at DARPA, she
extended the then new concept of Virtual Worlds to education, business and
research environments. Recently she is combining reflective architectures
with European Organic Computing approaches that emphasize the
self-organizational properties of biologically-inspired architectures and
operating systems to develop new cyber-security approaches and healthcare
architectures. Among her honors, she received the Award in Technology at
2008 Telluride Technology Festival. Other past awardees include Vint Cerf,
Murray Gellman, Charles Townes, and Freeman Dyson.

-- 
Luca Rossi

Lecturer in Computer Science
School of Engineering and Applied Science
Aston University
Web: http://www.cs.aston.ac.uk/~rossil/ <http://www.cs.bham.ac.uk/~rossil/>
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