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</o:shapelayout></xml><![endif]--></head><body lang=EN-GB link="#0563C1" vlink="#954F72" style='word-wrap:break-word'><div class=WordSection1><p class=Firstparagraph style='line-height:normal'>Dear all,<o:p></o:p></p><p class=Firstparagraph style='line-height:normal'><o:p> </o:p></p><p class=Firstparagraph style='line-height:normal'>Some of you may be interested in today’s Analogical Minds Seminar with Dr Shiwali Mohan:<o:p></o:p></p><p class=Firstparagraph style='line-height:normal'><o:p> </o:p></p><p class=Firstparagraph style='line-height:normal'>“Using Insights from Analogical Minds to Build Interactive Task Learning Agents”<o:p></o:p></p><p class=Firstparagraph style='line-height:normal'>Dr Shiwali Mohan, Palo Alto Research Center<o:p></o:p></p><p class=Firstparagraph style='line-height:normal'>Thursday 30th March, 6:00 pm - 7:30 pm US PDT (9:00 am - 10.30 am in Beijing)<o:p></o:p></p><p class=Firstparagraph style='line-height:normal'><o:p> </o:p></p><p class=Firstparagraph style='line-height:normal'>Zoom link to attend can be found on our World Wide Neuro page: <a href="https://www.world-wide.org/seminar/9061/">https://www.world-wide.org/seminar/9061/</a><o:p></o:p></p><p class=Firstparagraph style='line-height:normal'>Seminar info: <a href="http://www.analogicalminds.com">www.analogicalminds.com</a> <o:p></o:p></p><p class=Firstparagraph style='line-height:normal'><o:p> </o:p></p><p class=Firstparagraph style='line-height:normal'>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.<o:p></o:p></p><p class=Firstparagraph style='line-height:normal'><o:p> </o:p></p><p class=Firstparagraph style='line-height:normal'>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.<o:p></o:p></p><p class=Firstparagraph style='line-height:normal'><o:p> </o:p></p><p class=Firstparagraph style='line-height:normal'>Best wishes,<o:p></o:p></p><p class=Firstparagraph style='line-height:normal'>Matt Slocombe<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal><o:p> </o:p></p></div></body></html>