Max Kleiman-Weiner
@maxkw.bsky.social
4.2K followers 370 following 430 posts
professor at university of washington and founder at csm.ai. computational cognitive scientist. working on social and artificial intelligence and alignment. http://faculty.washington.edu/maxkw/
Posts Media Videos Starter Packs
Pinned
maxkw.bsky.social
Our new paper is out in PNAS: "Evolving general cooperation with a Bayesian theory of mind"!

Humans are the ultimate cooperators. We coordinate on a scale and scope no other species (nor AI) can match. What makes this possible? 🧵

www.pnas.org/doi/10.1073/...
Evolving general cooperation with a Bayesian theory of mind | PNAS
Theories of the evolution of cooperation through reciprocity explain how unrelated self-interested individuals can accomplish more together than th...
www.pnas.org
Reposted by Max Kleiman-Weiner
kjha02.bsky.social
Forget modeling every belief and goal! What if we represented people as following simple scripts instead (i.e "cross the crosswalk")?

Our new paper shows AI which models others’ minds as Python code 💻 can quickly and accurately predict human behavior!

shorturl.at/siUYI%F0%9F%...
maxkw.bsky.social
New paper challenges how we think about Theory of Mind. What if we model others as executing simple behavioral scripts rather than reasoning about complex mental states? Our algorithm, ROTE (Representing Others' Trajectories as Executables), treats behavior prediction as program synthesis.
maxkw.bsky.social
Definitely, we should look closer at sample complexity for training but for things like webnav there are massive datasets so could be good fit.
maxkw.bsky.social
In some sense, yes, in that you need diverse trajectories of the agent's behavior in different contexts, but you don't need to have access to those goals, or even the distribution, and the agent might be doing non-goal-directed behavior, such as exploration.
maxkw.bsky.social
When values collide, what do LLMs choose? In our new paper, "Generative Value Conflicts Reveal LLM Priorities," we generate scenarios where values are traded off against each other. We find models prioritize "protective" values in multiple-choice, but shift toward "personal" values when interacting.
andyliu.bsky.social
🚨New Paper: LLM developers aim to align models with values like helpfulness or harmlessness. But when these conflict, which values do models choose to support? We introduce ConflictScope, a fully-automated evaluation pipeline that reveals how models rank values under conflict.
(📷 xkcd)
maxkw.bsky.social
Very cool! Thanks for sharing! Would be interesting to compare your exploration ideas on open ended tasks beyond little alchemy with EELMA
maxkw.bsky.social
Excited by our new work estimating the empowerment of LLM-based agents in text and code. Empowerment is the causal influence an agent has over its environment and measures an agent's capabilities without requiring knowledge of its goals or intentions.
maxkw.bsky.social
Claire's new work showing that when an assistant aims to optimize another's empowerment, it can lead to others being disempowered (both as a side effect and as an intentional outcome)!
claireyang.bsky.social
Still catching up on my notes after my first #cogsci2025, but I'm so grateful for all the conversations and new friends and connections! I presented my poster "When Empowerment Disempowers" -- if we didn't get the chance to chat or you would like to chat more, please reach out!
Person standing next to poster titled "When Empowerment Disempowers"
Reposted by Max Kleiman-Weiner
claireyang.bsky.social
Still catching up on my notes after my first #cogsci2025, but I'm so grateful for all the conversations and new friends and connections! I presented my poster "When Empowerment Disempowers" -- if we didn't get the chance to chat or you would like to chat more, please reach out!
Person standing next to poster titled "When Empowerment Disempowers"
maxkw.bsky.social
It’s forgivable =) We just do the best we can with what we have (i.e., resource rational) 🤣
Reposted by Max Kleiman-Weiner
mehr.nz
samuel mehr @mehr.nz · Jul 31
lol this may be the most cogsci cogsci slide I've ever seen, from @maxkw.bsky.social

"before I got married I had six theories about raising children, now I have six kids and no theories"......but here's another theory #cogsci2025
Max giving a talk w the slide in OP
maxkw.bsky.social
Quantifying the cooperative advantage shows why humans, the most sophisticated cooperators, also have the most sophisticated machinery for understanding the minds of others. It also offers principles for building more cooperative AI systems. Check out the full paper!

www.pnas.org/doi/10.1073/...
Evolving general cooperation with a Bayesian theory of mind | PNAS
Theories of the evolution of cooperation through reciprocity explain how unrelated self-interested individuals can accomplish more together than th...
www.pnas.org
maxkw.bsky.social
Finally, when we tested it against memory-1 strategies (such as TFT and WSLS) in the iterated prisoner's dilemma, the Bayesian Reciprocator: expanded the range where cooperation is possible and dominated prior algorithms using the *same* model across simultaneous & sequential games.
maxkw.bsky.social
Even in one-shot games with observability, the Bayesian Reciprocator learns from observing others' interactions and enables cooperation through indirect reciprocity
maxkw.bsky.social
In dyadic repeated interactions in the Game Generator, the Bayesian Reciprocator quickly learns to distinguish cooperators from cheaters, remains robust to errors, and achieves high population payoffs through sustained cooperation.
maxkw.bsky.social
Instead of just testing on repeated prisoners' dilemma, we created a "Game Generator" which creates infinite cooperation challenges where no two interactions are alike. Many classic games, like the prisoner’s dilemma or resource allocation games, are just special cases.
maxkw.bsky.social
It uses theory of mind to infer the latent utility functions of others through Bayesian inference and an abstract utility calculus to work across ANY game.
maxkw.bsky.social
We introduce the "Bayesian Reciprocator," an agent that cooperates with others proportional to its belief that others share its utility function.
maxkw.bsky.social
Classic models of cooperation like tit-for-tat are simple but brittle. They only work in specific games, can't handle noise and stochasticity and don't understand others' intentions. But human cooperation is remarkably flexible and robust. How and why?
maxkw.bsky.social
This project was first presented back in 2018 (!) and was born from a collaboration between Alejandro Vientos, Dave Rand @dgrand.bsky.social & Josh Tenenbaum @joshtenenbaum.bsky.social
maxkw.bsky.social
Our new paper is out in PNAS: "Evolving general cooperation with a Bayesian theory of mind"!

Humans are the ultimate cooperators. We coordinate on a scale and scope no other species (nor AI) can match. What makes this possible? 🧵

www.pnas.org/doi/10.1073/...
Evolving general cooperation with a Bayesian theory of mind | PNAS
Theories of the evolution of cooperation through reciprocity explain how unrelated self-interested individuals can accomplish more together than th...
www.pnas.org
Reposted by Max Kleiman-Weiner
kartikchandra.bsky.social
As always, CogSci has a fantastic lineup of workshops this year. An embarrassment of riches!

Still deciding which to pick? If you are interested in building computational models of social cognition, I hope you consider joining @maxkw.bsky.social, @dae.bsky.social, and me for a crash course on memo!
cogscisociety.bsky.social
#Workshop at #CogSci2025
Building computational models of social cognition in memo

🗓️ Wednesday, July 30
📍 Pacifica I - 8:30-10:00
🗣️ Kartik Chandra, Sean Dae Houlihan, and Max Kleiman-Weiner
🧑‍💻 underline.io/events/489/s...
Promotional image for a #CogSci2025 workshop titled “Building computational models of social cognition in memo.” Organized and presented by Kartik Chandra, Sean Dae Houlihan, and Max Kleiman-Weiner. Scheduled for July 30 at 8:30 AM in room Pacifica I. The banner features the conference theme “Theories of the Past / Theories of the Future,” and the dates: July 30–August 2 in San Francisco.