Welcome to our monthly digest, where you can catch up with any AIhub stories you may have missed, peruse the latest news, recap recent events, and more. This month, we delved into the history of RoboCup, learned about time series, studied multiplicity, and found out more about Theory of Mind. RoboCup is an international competition that promotes and advances robotics and AI through the challenges presented by its various leagues. We got the chance to sit down with Professor Manuela Veloso, one of RoboCup's founders, to find out more about how it all started, how the community has grown over the years, and the vision for the future. What we've learned from 25 years of automated science, and what the future holds We're excited to launch a new series, where we'll be speaking with leading researchers to explore the breakthroughs driving AI and the reality of the future promises, to give you an inside perspective on the headlines.

RoboCup is an international competition that promotes and advances robotics and AI through the challenges presented by its various leagues. We got the chance to sit down with Professor Manuela Veloso, one of RoboCup's founders, to find out more about how it all started, how the community has grown over the years, and the vision for the future. I think it would be very interesting to go right back to the beginning and hear how RoboCup got started. What was the initial idea, and how did it get set up? So we are talking about the mid-90s. In terms of the research in those days, it was the beginning of the internet and many AI and computer science researchers were focused on the internet, first on sophisticated search algorithms, on natural language understanding, on information retrieval, and then on software agents and machine learning applied to digital information. From what I recall, there was a smaller group of researchers who were interested in actual, physical robots, and in particular in AI and robotics.

In a special award session, the best papers of the conference were announced. The AAAI-2023 outstanding paper award went to Joar Skalse and Alessandro Abate for their work Misspecification in Inverse Reinforcement Learning. The AAAI-2023 outstanding student paper award was given to Decorate the Newcomers: Visual Domain Prompt for Continual Test Time Adaptation, authored by Yulu Gan, Yan Bai, Yihang Lou, Xianzheng Ma, Renrui Zhang, Nian Shi, and Lin Luo. There were also 12 distinguished paper award winners, the details of which can be found here. As well as these best paper awards, a number of prestigious AAAI awards were presented at the conference. These included the AAAI Award for Artificial Intelligence for the Benefit of Humanity, which was won by Tuomas Sandholm. You can find out more about this prize, and the others awarded, here. There will be plenty more content to come as we continue to cover the conference, and hear from participants about their work. You can find our conference coverage here, and this collection will be updated as soon as we add new content.

Manuela Veloso won the 2023 Robert S. Engelmore Memorial Award, which recognises outstanding contributions to automated planning, machine learning and robotics, their application to real-world problems and extensive service to the AI community. The winner of this prize is invited to give a lecture at the annual conference on Innovative Applications of Artificial Intelligence (IAAI) (which is collocated with the AAAI Conference on Artificial Intelligence, and this year took place from 7-14 February). Manuela's talk focussed on her research on autonomous robots, and how she has transferred expertise and knowledge from that domain to the field of AI in finance. In both cases, humans interact with AI systems to jointly solve complex end-to-end problems. Manuela began her research career investigating autonomous robots.

She has consistently pursued research and teaching in artificial intelligence, robotics and machine learning, and has advised 45 CMU Ph.D.

Nominations are solicited for the 2022 ACM SIGAI Autonomous Agents Research Award. This award is made for excellence in research in the area of autonomous agents. It is intended to recognize researchers in autonomous agents whose current work is an important influence on the field. The award is an official ACM award, funded by an endowment created by ACM SIGAI from the proceeds of previous Autonomous Agents conferences. The recipient of the award will receive a monetary prize and a certificate, and will be invited to present a plenary talk at the AAMAS 2022 conference in Auckland, New Zealand.

Karl Tuyls, a former RoboCup participant and local chair of the 2D simulation league (2013), recently published an article along with his colleagues at DeepMind called Game plan: what AI can do for football, and what football can do for AI. Karl Tuyls: The long-term vision in this project is to advance research in multi-agent decision-making by building an automated video assistant coach for real-world soccer (or football), that can help coaches and teams in analyzing games, making tactical choices in a match (e.g. in set pieces situations), improve their overall game-play, and even assist with in-game analysis and decision-making. Next to that one can also think additionally of human factors like injury prediction and the search for new players. For this we are blending research from game theory, vision and machine learning. So far our work has focused on game-theoretic analysis of set pieces and on trajectory predictions of players and ball with the purpose to allow for counterfactual reasoning (what happens if player X moves in direction Y, for example).

Most large banks in the US are pursuing AI fairly assiduously, but JPMorgan Chase stands out for the depth of its commitment to the technology, the breadth of projects it has adopted, and the focus on driving actual business change from its AI initiatives. The Bank, the largest in the US and 6th largest in the world in terms of total assets, has AI projects or production applications in all the usual areas of banking: risk, fraud prevention, marketing, investment banking, wealth management advice, trading, back office automation, and customer engagement (particularly in the corporate banking area thus far). But JPMorgan Chase distinguishes itself from other banking firms in its level of investment, its hiring of AI academic stars, and its coordinated approach to the management of AI and analytics. JPMorgan Chase spends $11 billion a year on technology, and about half of that amount is devoted to research on new and emerging technologies. Its research investments cover a wide variety of domains, including investments in AI startups and AI-based hedge funds.

From beating us at the game of GO, to recreating paintings by Van Gogh, algorithms are all around us. Artificial Intelligence is no longer science fiction as we are witnessing breakthrough after breakthrough. What most of these innovations have in common is that they make use of a technique called "deep learning." Earlier I had the chance to ask world renowned AI experts about their favorite algorithms in general. This time we will focus on deep learning!

Artificial intelligence is in our phones, beginning to control our money, and giving robots some decision-making powers. But Carnegie Mellon professor Manuela Veloso, incoming head of JPMorgan's AI research division, is frustrated that things aren't further along. "I came from the Boston airport last night and I didn't see a single mobile robot anywhere on my way here," she said. After her decades of work in AI research, Veloso is ready to see more mobile robots in our everyday lives. She envisions a future where everything with wheels, from suitcases to shopping carts, will automatically follow you at a single command.