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IEEE CIS Newsletter, Issue 108, January 2022 (1/2)

The Changing of the Guard

Hi all,

As mandated in our ByLaws, the CIS President is elected by the AdCom with a term of two years. It seems like only yesterday that Bernadette Bouchon-Meunier began her Presidency, but now it’s my turn. Talk about your “hard act to follow!” I have great admiration and affection for Bernadette, who led us through the unprecedented time of the COVID-19 pandemic with such grace and acumen. I have been fortunate to have worked with her over the years in several capacities, have had an inside view of CIS as her President-elect in 2021, but most of all to be able to call her “mon amie.” She’ll continue to be a fierce advocate for diversity and inclusion in CIS and to provide leadership as Past President in 2022 to my great relief. Bernadette followed a long line of dedicated and innovative Presidents; CIS has been fortunate for their leadership. Now it’s my turn “in the barrel.” The good news for me (and for you!) is that we have a large cast of extremely talented folks who carry the brunt of the organizational load. The Vice Presidents are energetic and committed. Besides Finance, Publications, Conferences, Technical Activities, Education, and Membership, 2022 will see a VP in a new focus area, Industry and Government Activities. The leadership of the CIS standing committees, subcommittees, adhoc committees, EiCs and AEs do so much to ensure that all goes well within CIS. Also, we are blessed with three outstanding IEEE staff members who keep the wheels of CIS rolling smoothly.

The Society is only as vibrant as its volunteers. We need, and thrive on, volunteers from the level of Student member through our Life Fellows. It’s vitally important to continue to broaden the group of bright and energetic people to help move CIS forward. So, whatever your passion, CIS has a place for you. Take some time to explore the CIS website to find your place(s) and join the fun. Please feel free to contact me ([email protected]) or any of the Vice Presidents with suggestions/comments, and most importantly, to express your willingness to be of service. We value your membership and hope to hear from you.

Jim Keller
CIS President, 2022-2023
Research Frontier

Advances in Memetic Automaton: Toward Human-Like Autonomous Agents in Complex Multi-Agent Learning Problems

A visual representation of AI.
 A clear white box model containing a digitized brain, with the letters X, A & I etched on the top of the boxThe meme-centric memetic automaton (MA) was recently proposed as an adaptive entity or a software agent wherein memes are defined as the building blocks of knowledge. The conceptualization of MA has led to the development of a large number of potentially rich meme-inspired designs that form a cornerstone of memetic computation as tools for problem-solving. In this study, we investigate the use of memetic multi-agent systems to develop more intelligent and human-like autonomous agents by taking MA as the essential backbone of the agent. Taking inspiration from a psychological Broadbent-Treisman Attenuation Model, we propose an attention intensity control method in meme expression for enhancing agents’ perception of the value of all kinds of information captured from the environment, hence leading to a greater capability of meme knowledge generalization. Our particular focus is placed on the design of meme selection for more effective knowledge transmission across the population. To this end, we introduce a bidirectional imitation strategy based on agents’ estimation of the importance and/or uncertainty of decision making in a dynamic environment. Experiments on a minefield navigation simulation as well as a commercial video game demonstrate the superior performance of our proposed method compared to state-of-the-art methods. Read More

IEEE Computational Intelligence Magazine, November 2021


Explanation as a Social Practice: Toward a Conceptual Framework for the Social Design of AI Systems

AI Learning and Artificial Intelligence Concept.
 Business, modern technology, internet and networking concept.
 3d illustrationThe recent surge of interest in explainability in artificial intelligence (XAI) is propelled by not only technological advancements in machine learning but also by regulatory initiatives to foster transparency in algorithmic decision making. In this article, we revise the current concept of explainability and identify three limitations: passive explainee, narrow view on the social process, and undifferentiated assessment of explainee’s understanding. In order to overcome these limitations, we present explanation as a social practice in which explainer and explainee co-construct understanding on the microlevel. We view the co-construction on a microlevel as embedded into a macrolevel, yielding expectations concerning, e.g., social roles or partner models: typically, the role of the explainer is to provide an explanation and to adapt it to the current level of explainee’s understanding; the explainee, in turn, is expected to provide cues that direct the explainer. Building on explanations being a social practice, we present a conceptual framework that aims to guide future research in XAI. The framework relies on the key concepts of monitoring and scaffolding to capture the development of interaction. We relate our conceptual framework and our new perspective on explaining to transparency and autonomy as objectives considered for XAI. Read More

IEEE Transactions on Cognitive and Developmental Systems, September 2021


Towards Machine Learning as an Enabler of Computational Creativity

Light Bulb Ideas Creative Diagram Concept stock photoComputational creativity composes a collection of activities that are capable of achieving or simulating behaviors which can be deemed creative. A frequently articulated criticism for related systems is that the creative capability remains with the software designer rather than the computational creative system itself. The rise of machine learning enables new ways of combining, exploring, and transforming conceptual spaces to achieve creative results. This paper demonstrates that the learning occurring within the computational machine through machine learning enables creative capabilities therein, allowing the computational creative system to be more creative on its own than ever before. Thus, we perceive machine learning as a key enabler of computational creativity. In this conceptual study, we consolidate research from the Computer Science, Computational Creativity, and Information Systems communities, which has been treated separately so far. Read More

IEEE Transactions on Artificial Intelligence, July 2021

Member Activities
IEEE CIS at LinkedIn

Are you a LinkedIn user? If so, please follow our new page.  Here, you will find conference announcements and exciting member information. And if you want to get involved in the conversation, don’t forget to follow our Twitter account @ieeecis.

For our conference organisers, if you are supporting the development of websites or social media accounts, don’t forget to check out important IEEE information for volunteers.

Meet: Jerry Mendel, IEEE Lotfi A. Zadeh Pioneer Award 2021

Jerry MendelJerry Mendel, a long-time member of the CIS, has received the IEEE Lotfi A. Zadeh Pioneer Award – maintained by the IEEE Systems, Man, and Cybernetics Society – for developing and promoting Type-2 fuzzy logic. The IEEE Lotfi A. Zadeh Pioneer Award honors a person or persons with outstanding and pioneering contributions to academic and/or industrial research in systems science and engineering, human-machine systems, and/or cybernetics (established in 2014), made at least 15 years prior to the award date. Past awardees are: 2017—Lotfi Zadeh (honorary) and Michio Sugeno, and 2018—Ronald Yager. 

What is your title, and place of work? (or Technical Field of Research)?

I am an Emeritus Professor of Electrical Engineering, Viterbi School of Engineering 
University of Southern California

Although retired since 2018, I continue to research fuzzy sets and systems (mainly type-2) either individually or with colleagues from around the World.

I was a member of Fuzzy Systems TC from 2001–2015, and its Chair from 2003 –2007.

AdCom Member from 2004–2009 and 2011–2013, Chairman of Task Force on Computing With Words for the Fuzzy Systems TC from 2008-2010, AE of IEEE Trans. on Fuzzy Systems from 1994–1995 and 1999–2016.

How long have you been a member of CIS and what was the reason you chose to join IEEE CIS?

I have been a member of CIS from its inception. I joined because it covered my technical interests.

What Computational Intelligence society committee do you serve?

In the past, I used to be in many committees in CIS.

Presently, I am a member of the Continuing Education Sub-Committee and the Industrial Activities Committee (before I began my academic career I worked in industry for 11 years).

What have you learned from your experience and how has it helped you professionally?

I have been active in IEEE Societies for my entire career. Prior to my joining CIS I had been President of the IEEE Control Systems Society and EIC of the IEEE Transactions on Automatic Control. Working with the leaders and luminaries of a field has been a very rewarding experience. Being the Chair of a TC or a TF has provided me with opportunities to influence some research directions. I have also been able to make some connections with colleagues who then work with me jointly on research projects that are of mutual interest.

What has been the most fun/rewarding thing about being a volunteer for the IEEE Computational Intelligence Society? What have you enjoyed the most?

Meeting and interacting with so many interesting people.

I was asked to chair a sub-committee for creating a competition for a video that would explain what a fuzzy set is, with monetary awards to the winners. Something like this had not been done before in the CIS, and I really like doing something that no one has done before. You can let your creative juices flow. This gave me an opportunity to work with some very talented younger members of the CIS. It was an amazingly fun project, and there are now two winning You-Tube videos: “An Egg-Boiling Fuzzy Logic Robot” and “Fuzzy Logic: An Introduction.”

I have also enjoyed going to dinners with CIS colleagues after adCom meetings.

Tell us something about you that we don’t know.

I am an avid Bridge player, and have been playing for close to 60 years.


Live Webinar

Computational Intelligence for Disaster Planning and Mitigation

Date: Wednesday, 26 January 2022
Time: 10:00 AM - 11:00 AM EST


Infrastructure planning and restoration following a disaster is a complex problem requiring the integration of multiple data types and the evaluation of complex and potentially nonlinear relationships. This research uses publicly available data sets shared by the United States Geological Survey (The National Map, Digital Elevation Models, seismic data), the United States Army Corps of Engineers (River Discharge data, Lock & Dam and Levee inventory), and the U.S. National Weather Service (rainfall data, predicted weather patterns). This body of work examines evolutionary computation for infrastructure restoration planning in the aftermath of tornadoes and earthquakes. The use of neural networks is considered to predict changing water levels to capture the timing and impact of flooding and flash flooding events on transportation infrastructure. Read more


Featured Speaker

Prof. Steven M. Corns
Prof. Steven M. Corns

Steven M. Corns is an Associate Professor of Engineering Management and Systems Engineering at Missouri University of Science and Technology. He received his PhD degree in mechanical engineering from Iowa State University in 2008.


Live Webinar

Autonomous Bootstrapping of Collective Motion Behaviours for Swarming Robots

Date: Monday, 21 February 2022
Time: 9:00 PM - 10:00 PM EST


Collective behaviours such as swarm formations of autonomous agents offer the advantages of efficient movement, redundancy, and potential for human guidance of a single swarm organism. However, with the explosion in hardware platforms for autonomous vehicles, swarm robotic programming requires significant manual input for each new platform. This talk introduces two developmental approaches to evolving collective behaviours whereby the developmental process is guided by a task-non-specific value system. Two value systems will be considered: the first based on a survey of human perception of swarming and the second based on a computational model of curiosity. Unlike traditional approaches, these value systems do not need in advance the precise characteristics of the intended swarming behaviours. Read more


Featured Speaker

Prof. Kathryn Kasmarik
Prof. Kathryn Kasmarik

Kathryn Kasmarik is a Professor of Computer Science at the University of New South Wales, Australian Defence Force Academy (UNSW Canberra). Kathryn completed a Bachelor of Computer Science and Technology at the University of Sydney, including a study exchange at the University of California, Los Angeles (UCLA). She graduated with First Class Honours and the University Medal in 2002. She completed a PhD in Computer Science through the National ICT Australia and the University of Sydney in 2007. She moved to UNSW Canberra in 2008.


Live Webinar

Generation Hyper-Heuristics for Automated Design, Configuration and Selection

Date: Tuesday, 22 March 2022
Time: 7:00 AM - 9:00 AM EDT


Automated algorithm design, configuration and selection of machine learning and search algorithms (AutoDes) has made an impact on computational intelligence contributing to the advancement of the field. Generation hyper-heuristics, while in some ways still in their infancy, have proven to be effective for AutoDes. The application of generation hyper-heuristics in AutoDes range from creating new heuristics and operators to generating components of algorithms. The webinar will present an overview of generation hyper-heuristics in AutoDes, highlighting the advances and challenges. The webinar will also highlight future research directions in this field. Read more


Featured Speaker

Prof. Nelishia Pillay
Prof. Nelishia Pillay

Nelishia Pillay is a Professor at the University of Pretoria, South Africa. She holds the Multichoice Joint-Chair in Machine Learning and SARChI Chair in Artificial Intelligence. She is chair of the IEEE Technical Committee on Intelligent Systems Applications, IEEE Task Force on Hyper-Heuristics and the IEEE Task Force on Automated Algorithm Design, Configuration and Selection.

Educational Activities
2022 Graduate Student Research Grants: Call for Applications

The IEEE Computational Intelligence Society (CIS) funds scholarships for deserving undergraduate, graduate and PhD students who need financial support to carry out their research during an academic break period. The primary intent of these scholarships is to cover the expenses related to a visit to another university, institute, or research agency for collaboration with an identified researcher in the field of interest of the applicant. Funds can be used to cover travel expenses as well as certain living expenses (such as housing). The field of interest of applicants is open but should be connected with an identifiable component of the CIS (neural networks, fuzzy systems, or evolutionary computation). The call for the next round of applications will be announced soon and will have a deadline for submission of 15 March 2022.

More information on the scheme can be found on the CIS Graduate Student Research Grants webpage.

Editor Bing Xue
Victoria University of Wellington, New Zealand
Email: [email protected]

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