A proposal for deflating deflationary accounts of free will; consciousness and the readiness to act

Hello, this is ActonFlab guest stream number 21.1. It's April 21st, 2022, and we're here with Shannon Proksh, and Shannon will be giving a talk, Coordination Dynamics of Multi-Agent Interaction. The talk will happen for maybe around an hour, and then there'll be time for Q&A, so feel free to ask any questions in the chat during. So off to you, Shannon, looking forward to this talk, and thanks again for joining on ActonFlab. Awesome, thanks so much. So I'm Shannon, Daniel's already given you the title of our talk, and I'm coming to you from the University of California in Merced, where I'm a PhD candidate, and I'll actually be defending this summer, so maybe the next time you hear from me, I'll be talking to you from Augustana University, where I will be starting a tenure-track professor position later this fall as an assistant professor of psychology and neuroscience. Oh, applause, nice, thanks. So that said, I'm not going to talk to you about neuroscience today. I'm going to talk to you a little bit about the behavior of crowds, and I stole this roadmap idea from previous Active Inference Lab sessions, and this is kind of outlining where we'll be going today. So first, the first thing we're going to do is really dig into a little bit of theory and data. I'm going to give a bit of a brief introduction to multi-agent interaction and what kind of human behavior I'm interested in. And I'm going to walk through a couple of ways that active inference folks might be interested in crowd dynamics and behavior, but primarily, I'm going to be focusing on dynamical systems theory and the notion of synergies and the tools that come along with these concepts. And then finally, I'm going to show you a model system where we apply these tools to a system of coupled metronomes before I look at some empirical data from real world interaction, musical performance, and also of crowds cheering at a basketball game. So first, what is multi-agent interaction? This is simply an interaction that's happening between two or more agents. In our case, we're looking at people and each of these people, they'll have their own personal goals and behaviors, but their individual behaviors are influenced in some way by interacting with other agents in their shared environment. And I want to talk about two forms of multi-agent coordination today. And the best way to introduce this is through a short thought experiment. So I'll just have you imagine the sounds of a crowded coffee shop. Consider how individuals in that coffee shop might be interacting with each other. There might be some small groups, there might be pairs, but mostly it's many individuals engaging in small temporary interactions. And these individuals aren't coordinating with every other individual in some sort of cohesive coffee shop group. They're just a jumble of individual individuals who are cohabiting a shared space. Now instead, imagine the audience on the floor of a rock concert. They're cheering or singing along with the artists on the stage. And alternatively, imagine the fan section at your favorite sporting event emerging into a synchronous chant or a chorus of resounding booze. Imagine how individuals in these large crowds might be interacting with each other. As they cheer, sing, chant, or boo, they're all sharing in similar behavioral states, engaging in similar actions. They're likely sharing similar physiological states, like breathing rates, and neural states as well. These crowds are changing together in time. They're behaving and they're coordinating like one large interdependent group. And you could refer to these as shared acoustic spaces. And they include various levels of interaction from dyads, pairs of individuals, or larger and larger groups. And I might even call these acoustic social worlds. The acoustic signal that's generated by these crowds, it carries some information about their behavioral dynamics that were employed in creating that signal. And the sounds these…