https://members.femto-st.fr/julien-bourgeois
https://www.programmable-matter.com
Technological advances, especially in the miniaturization of robotic devices foreshadow the emergence of large-scale ensembles of small-size resource-constrained robots that distributively cooperate to achieve complex tasks. These ensembles are formed by independent, intelligent, and communicating units which act as a whole forming a programmable material i.e., a material able to autonomously change its shape.
In my talk, I will present our research effort in building a modular robot composed of mm-scale units. We use micro-technology to scale down the size of each element, and we study geometry, structure, actuation, power, electronics, and integration. We develop multi-agent algorithms to scale up in the number of managed robots to perform synchronization, leader election, self-assembly and self-reconfiguration. As multi-agent systems are by essence decentralized, they are the best candidate to manage these distributed robotic systems.
Large language models have stretched our beliefs on what kind of machine intelligence is possible. However, there are still practical needs in several fields of computing to align artificial intelligence (AI) with human intelligence.
In this talk, I will discuss and problematize:
I will give insights on how cognitive mimetics can inspire AI solutions and review on-going research on modeling human intelligence as computational rationality with reinforcement learning agents in our cognitive science research group at University of Jyväskylä.
In a world where AI is increasingly prevalent, it is crucial to create AI models that can understand social dynamics and interact with people in social settings. In this presentation, I will discuss the development of social agents and their practical applications in areas like games and human-robot interaction. I will share examples of my research, discussing the different roles agents can play in games, some building blocks for the agents’ social models, and the use of robots as team leaders and advisors in workplaces. The talk highlights the importance of giving agents social skills to improve user experience and enable better interactions between humans and machines.
Generative AI systems such as ChatGPT are already disrupting education. They can write essays for students, summarise scientific texts, produce lesson plans, engage in conversations, and draft academic papers. New hybrid systems such as Auto-GPT extend the capabilities of generative AI, to interpret goals, form plans, enact tasks and access external tools such as web browsers and databases.
In this presentation I will introduce the capabilities and limitations of current generative AI and discuss implications for education. The talk will cover: how humans and AI can learn together, future roles for AI in education, new educational generative AI systems, and ethics of learning with AI. Rather than seeing AI as a challenge to traditional education, we should prepare students for a future where AI is a tool for creativity, to be operated with great care and awareness of its limitations.