Christian Guckelsberger

5/5 Collaboration between @aalto.fi and @oistedu.bsky.social, supported by Aalto Science Institute (ASci) and the Helsinki Institute for Information Technology (HIIT).

4/5 This work contributes to a young research agenda seeking to understand creativity beyond the realm of humans or highly developed animals. We argue for the SO model as a fascinating candidate to study the effect of learning on creativity from the bottom up - in life as it is and as it could be.

3/5 More specifically, we demonstrate that modifying the SO model learning parameters gives rise to four different regimes that can account for both creative products and inconclusive outcomes, thus providing a framework for studying and understanding the creative potential of learning systems.

2/5 Developed to model complex adaptive systems in ALife and advocated as a candidate for minimal agency, the Self-Optimization (SO) model can be considered as the 3rd operational mode of the classical Hopfield Network, leveraging the power of associative memory to enhance optimization performance.

1/5 Now in Artificial Life: our research on the creativity of unsupervised learning! Core finding: a simple model of attractor networks with Hebbian learning is sufficient to constitute a (minimal) creative process, yielding creative products as solutions of the optimization. doi.org/10.1162/ARTL...

Ethics is not a 15-minute box-ticking exercise — FCAI Responsible AI development requires continuous, critical ethical thinking from everyone involved in creating technology.

Read the blog of the Ethics Advisory Board of Finnish Center for Artificial Intelligence about the need to incorporate training and discussions in AI ethics in the AI-related doctoral student's curriculum. fcai.fi/eab-blog/eth... Written together with colleagues listed in the comments.

4/4 Locally, we're part of a rich AI research ecosystem, including the Finnish Center of AI (FCAI), Helsinki Institute for Information Technology (HIIT) @icthiit.bsky.social and the Finnish @ellis.eu institute, a world-class research hub in AI and machine learning.

3/4 You can work w/travel to our fantastic collaborators Natasha Jaques @natashajaques.bsky.social (Washington U./DeepMind), Sebastian Deterding @codingconduct.cc (Imperial College), Christoph Salge @christophsalge.bsky.social & Daniel Polani (UH), & Julian Togelius @togelius.bsky.social (NYU)!

2/4 The AIR group (www.autotelic.science) embraces diversity in research, thought and identity and has a track record of research on (computational) intrinsic motivation, bridging between AI, Psychology and Cognitive Science. Aalto University is 15 min away from Helsinki and surrounded by nature.

1/4 Join us and the Autotelic Interaction Research (AIR) group @aalto.fi / Finland to work on Computational Social Intrinsic Motivation (SIM) as PhD (4y) or postdoc (2y). Job ad w project description and application instructions: bit.ly/4jyNLGv. We're looking forward to learning about you!

5/5 🤝 A collaboration between Aalto University @aalto.fi and Imperial College @imperialcollegeldn.bsky.social, generously supported by the Research Council of Finland and Helsinki Institute for Information Technology @icthiit.bsky.social

4/5 📆 Catch us in person: We will be presenting this work first at RLDM @rldmdublin2025.bsky.social in June (in person) and then at CogSci @cogscisociety.bsky.social in July (likely remote). Please join us for exciting discussions of this research and the directions in which we take it next!

3/5 🤔 Why it matters: By matching psychological theories with AI models, we foster transparency and testability in motivation research. More generally, our work can support a cycle of theory development by inspiring new AI models and experimental designs, which can then be used to refine the theory.

2/5 🔎 Overview: We match models of intrinsic motivation from RL with 4 facets of competence identified in previous work: effectance, skill use, task performance & capacity growth. This uncovers previously hidden preconditions in SDT and supports refining our understanding of intrinsic motivation.

1/5 🌟 Our latest peer-reviewed research bridges psychology and AI/reinforcement learning (RL)! We explore how AI models of intrinsic motivation can formalise the "need for competence" in Self-Determination Theory (SDT), a very popular theory of human motivation. Preprint: arxiv.org/abs/2502.07423.

What Lives? A meta-analysis of diverse opinions on the definition of life The question of "what is life?" has challenged scientists and philosophers for centuries, producing an array of definitions that reflect both the mystery of its emergence and the diversity of discipli...

New preprint! arxiv.org/abs/2505.15849 : Reed Bender (www.linkedin.com/in/reed-bend...), Karina Kofman (www.linkedin.com/in/karina-ko...), @blaiseaguera.bsky.social
"What Lives? A meta-analysis of diverse opinions on the definition of life"

Interested in working on (computational) intrinsic motivation x design x architecture? A really cool PhD project coming up - UK residents only and supervised by @christophsalge.bsky.social! Ah, and I'll be co-supervising :) All info below - many opportunities to fit in your profile and ideas.

Why Self-Determination Theory Needs Computational Modelling: The Case of Competence and Optimal Challenge

by @codingconduct.cc E. Lintunen N. Aly @creativeendvs.bsky.social

osf.io/n6x8s/downlo...

3/3 Why it matters: Understanding how we judge machine-made art can guide HCI design, support fair system evaluations, and inspire co-creativity applications. More exploratory results in paper! Collaboration between @aalto.fi and @helsinki.fi, supported by HIIT and the Research Council of Finland.

2/3 We compared two drawing robots, a mechanical plotter and an anthropomorphized arm, creating the same still-life drawings. Surprisingly, differences in robot embodiment did not affect creativity ratings. But seeing the art being made, and what makes it, boosted how creative people perceived them.

1/3 Out now: new paper on people's perception of AI (robot) creativity! Core finding: we attribute more creativity to a creative act if people not only see the final artwork, but also its creation process & the robot making it. Video: vimeo.com/1073134853 Open-access paper: doi.org/10.1145/3711...

Winter 2025 - Researcher positions in AI and machine learning — FCAI

Fancy working with me and the Autotelic Interaction Research (AIR) group at Aalto University @aaltouniversity.bsky.social? Call for phd/postdoc/research fellow positions with the Finnish Center for Artificial Intelligence now open! Check autotelic.science for topic fit. fcai.fi/winter-2025-...

(3/3) We are now extending our proof-of-concept with more experiments, e.g. on transfer learning. A key challenge is quantifying the diversity of learned skills, and we look forward to distilling relevant insights for tackling this from interacting with the wider community!

(2/3) DP is a method for shaping goal selection in reinforcement learning based on an agent’s beliefs about how much pursuing the goals will diversify its skills. DP is applicable to a particular class of intrinsic rewards used to learn a repertoire of diverse skills without task-specific rewards.

(1/3) This week at #neurips2024: our work on "Diversity Progress” (DP) to improve unsupervised skill learning. Meet authors Erik Lintunen & Nadia Ady at the Intrinsically Motivated Open-ended Learning (IMOL) workshop: Sun 15th, 8:15+, West Meeting Room 217–219. Paper: openreview.net/forum?id=nz9...

I’m in Melbourne, visiting @jon-mcc.bsky.social at Sensilab / @monashuniversity.bsky.social (+ escaping Finnish winter!). I’ll be around for 2 more weeks-> email if you fancy a chat! A super fresh overview talk, covering 6 recent projects on #creativity #AI #HCI: sensilab.monash.edu/forums/three...

Hello back! :) I gave my mental health a break from social media and made time for my wonderful daughter, who has added an entire new dimension to my experience of life, which I'm so grateful for. Expect me to be rather quiet, and post mostly about fresh research, conferences and jobs.