Connectionists: Today's Analogical Minds Seminar: Dr Shiwali Mohan, "Using Insights from Analogical Minds to Build Interactive Task Learning Agents"

[Matthew Slocombe]

Dear all,

 

Some of you may be interested in today's Analogical Minds Seminar with Dr
Shiwali Mohan:

 

"Using Insights from Analogical Minds to Build Interactive Task Learning
Agents"

Dr Shiwali Mohan, Palo Alto Research Center

Thursday 30th March, 6:00 pm - 7:30 pm US PDT (9:00 am - 10.30 am in
Beijing)

 

Zoom link to attend can be found on our World Wide Neuro page:
https://www.world-wide.org/seminar/9061/

Seminar info: www.analogicalminds.com <http://www.analogicalminds.com>  

 

Abstract: Humans are natural teachers; learning through instruction is one
of the most fundamental ways that we learn. Interactive Task Learning (ITL)
is an emerging research agenda that studies the design of complex
intelligent robots that can acquire new knowledge through natural human
teacher-robot learner interactions. ITL methods are particularly useful for
designing intelligent robots whose behavior can be adapted by humans
collaborating with them. In this talk, I will summarize our recent findings
on the structure that human instruction naturally has and motivate an
intelligent system design that can exploit their structure. The system -
AILEEN - is being developed using the common model of cognition.
Architectures that implement the Common Model of Cognition - Soar, ACT-R,
and Sigma - have a prominent place in research on cognitive modeling as well
as on designing complex intelligent agents. However, they miss a critical
piece of intelligent behavior - analogical reasoning and generalization. I
will introduce a new memory - concept memory - that integrates with a common
model of cognition architecture and supports ITL.

 

Speaker bio: Dr. Shiwali Mohan is a senior member of research staff at Xerox
PARC. She received her B.E. in Instrumentation and Control Engineering from
Netaji Subhas Institute of Technology, Delhi University and her M.S. and
Ph.D. degrees in computer science from the University of Michigan, Ann Arbor
with a focus on artificial intelligence. Dr. Mohan studies the design and
analysis of collaborative human-AI systems. Her research brings together
methods from artificial intelligence (AI) and machine learning (ML) with
insights from human-centered sciences to design systems that can collaborate
with humans effectively. Her research has had an inter-disciplinary impact
and has been published at venues for research on AI, human cognition,
cognitive systems, human-computer interaction (HCI), medical informatics, AI
for social good, and robotics.

 

Best wishes,

Matt Slocombe

 

 

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