Kozzy Voudouris @kozzyvoudouris.bsky.social · 03/11/2025A great opportunity to work at the cutting edge of AI and cognitive science! 021 2
Reposted by Kozzy VoudourisFranziska Brändle @frabraendle.bsky.social · 02/10/2025What influences whether people have fun with a task? Our paper “Leveling up fun: learning progress, expectations and success influence enjoyment in video games” with @thecharleywu.bsky.social and @ericschulz.bsky.social now in Scientific Reports! rdcu.be/eI069 Paper summary below 1/4rdcu.beLeveling up fun: learning progress, expectations, and success influence enjoyment in video gamesScientific Reports - Leveling up fun: learning progress, expectations, and success influence enjoyment in video games 15917 59
Reposted by Kozzy VoudourisMilena Rmus @milenamr7.bsky.social · 22/09/2025Happy to announce our paper got accepted to #NeurIPS! @akjagadish.bsky.social @marvinmathony.bsky.social @ericschulz.bsky.social & Tobi Ludwig arxiv.org/abs/2502.00879arxiv.orgGenerating Computational Cognitive Models using Large Language ModelsComputational cognitive models, which formalize theories of cognition, enable researchers to quantify cognitive processes and arbitrate between competing theories by fitting models to behavioral data.... 1235 23
Reposted by Kozzy VoudourisMatishalin @matishalin.bsky.social · 18/09/2025Excited for this paper to be out, literal years of hard work by Kozzy. Excitingly, my first last author paper! This work came from joining the Kinds of Intelligence group at Cambridge and being given time by @martahalina.bsky.social to explore and cross disciplines. Hard work but very fun! 🧪 🤖🧠 063 6
Kozzy Voudouris @kozzyvoudouris.bsky.social · 18/09/2025@matishalin.bsky.social @martahalina.bsky.social 000 0
Kozzy Voudouris @kozzyvoudouris.bsky.social · 18/09/2025We find that recurrence confers a significant advantage for learning more complex grammars, but lamination does not. This work would not have been possible without Matishalin Patel, Colin Klein, Marta Halina, and Andrew Barron. You can check out our preprint here: arxiv.org/abs/2509.13968.arxiv.orgExploring Major Transitions in the Evolution of Biological Cognition With Artificial Neural NetworksTransitional accounts of evolution emphasise a few changes that shape what is evolvable, with dramatic consequences for derived lineages. More recently it has been proposed that cognition might also h... 140 4
Kozzy Voudouris @kozzyvoudouris.bsky.social · 18/09/20252) The evolution of lamination, in which information is processed by independent sub-components. We test these networks on artificial grammar learning tasks, for which the complexity of the problem can be precisely stated. 120 2
Kozzy Voudouris @kozzyvoudouris.bsky.social · 18/09/2025We focus on two transitions 1) The evolution of recurrent systems, in which information feeds back to earlier parts of the network. 120 2
Kozzy Voudouris @kozzyvoudouris.bsky.social · 18/09/2025In a new preprint, we explore this hypothesis with a computational approach. By systematically evolving neural nets with different structures, we measure whether key structural transitions improve performance on more complex problems, while controlling for the resources available to the network. 120 2
Kozzy Voudouris @kozzyvoudouris.bsky.social · 18/09/2025The arrangement of neurons is adjusted, using similar resources but opening up the possibility for more complex behaviour. This helps to explain the huge diversity of cognition we see across our planet: from nematodes 🪱 and box jellyfish 🪼 , to bees 🐝 , octopus 🐙 , chimpanzees 🐵 , and us 🙋 . 120 2
Kozzy Voudouris @kozzyvoudouris.bsky.social · 18/09/2025What if the same is true for the evolution of cognition? It has recently been argued that the evolution of brains across the animal kingdom can be characterised in terms of just a few major structural changes. 130 3
Kozzy Voudouris @kozzyvoudouris.bsky.social · 18/09/2025A prominent idea in biology tells us that evolution is not always incremental, but often involves a few important structural changes that open up phylogenetic possibility. Think: single cells ➡️ multicellular life. Solitary individuals ➡️ eusocial colonies. 131 3
Kozzy Voudouris @kozzyvoudouris.bsky.social · 03/09/2025That's certainly a hard part too, I can't deny that! 000 0
Kozzy Voudouris @kozzyvoudouris.bsky.social · 02/09/2025Thanks @dmoralesp.bsky.social, I'm interested to hear your thoughts! 000 0
Kozzy Voudouris @kozzyvoudouris.bsky.social · 02/09/2025You can check out the published article here (doi.org/10.1007/s105...) and a pre-print here (philsci-archive.pitt.edu/26165/). 030 3
Kozzy Voudouris @kozzyvoudouris.bsky.social · 02/09/2025This gives rise to an apparent, but ineffable, distinction between hypotheses. Crucially, this apparent distinction does not necessarily imply a distinction at the level of behavioural processes. 131 3
Kozzy Voudouris @kozzyvoudouris.bsky.social · 02/09/2025For decades, this distinction has been tacitly assumed but impossible to accurately define. I argue that the apparent distinction is actually an artefact of widespread analogical reasoning based on theories in human psychology and classic behaviourist associative learning theory. 141 4
Kozzy Voudouris @kozzyvoudouris.bsky.social · 02/09/2025I suggest that the widespread use of analogies explains away one of the most controversial debates in this field: whether associative learning and cognition are distinct behavioural processes. 141 4
Kozzy Voudouris @kozzyvoudouris.bsky.social · 02/09/2025In my latest thriller, published today in Biology and Philosophy, I argue that one useful hypothesis generation strategy in comparative psychology is analogical reasoning. 131 3
Kozzy Voudouris @kozzyvoudouris.bsky.social · 02/09/2025 The hypothesis space is so large and it requires us to eschew our human-centred expectations about behaviour and cognition. 121 2
Kozzy Voudouris @kozzyvoudouris.bsky.social · 02/09/2025Doing cognitive science on non-human systems like animals or artificial intelligence, brings inherent challenges. One of them is generating plausible alternative explanations for behaviour that can be tested empirically. 2153 15
Reposted by Kozzy Voudourislucaschubu.bsky.social @lucaschubu.bsky.social · 02/06/2025Excited to say our paper got accepted to ICML! We added new findings including this: models fine-tuned on a visual counterfactual reasoning task do not generalize to the underlying factual physical reasoning task, even with test images matched to the fine-tuning data set. 161 6
Kozzy Voudouris @kozzyvoudouris.bsky.social · 23/05/2025Many thanks to my coauthors @martahalina.bsky.social , @lucycheke.bsky.social, and Ben Farrar for working with me on this project. 011 1
Kozzy Voudouris @kozzyvoudouris.bsky.social · 23/05/2025You can check out the open-access paper here: psycnet.apa.org/fulltext/202...psycnet.apa.orgAPA PsycNet 121 2
Kozzy Voudouris @kozzyvoudouris.bsky.social · 23/05/2025We found that comparative psychologists have incredibly diverse attitudes to these methodological challenges. This suggests that there is still a lot of work for both psychologists and philosophers of science to do to clarify fundamental debates at the heart of comparative psychology research. 111 1
Kozzy Voudouris @kozzyvoudouris.bsky.social · 23/05/2025First, the apparent distinction between associative learning and cognition, and second, the question of whether some explanations of animal behaviour are simpler than others (often discussed with reference to Morgan's Canon). 111 1
Kozzy Voudouris @kozzyvoudouris.bsky.social · 23/05/2025We surveyed 220 practicing comparative psychologists, asking them questions about two key methodological challenges that define their science... 111 1
Kozzy Voudouris @kozzyvoudouris.bsky.social · 23/05/2025I am very pleased to announce that my paper "Morgan's Canon and the Associative-Cognitive Distinction Today: A Survey of Practitioners" was published this week in the Journal of Comparative Psychology. 131 3
Reposted by Kozzy VoudourisNature Reviews Psychology @natrevpsychol.nature.com · 13/05/2025Bringing comparative cognition approaches to AI systems Comment by Konstantinos Voudouris (@kozzyvoudouris.bsky.social), Lucy Cheke (@lucycheke.bsky.social) & Eric Schulz (@ericschulz.bsky.social) go.nature.com/43djJlv 0103 10
Reposted by Kozzy VoudourisOlivia Guest · Ολίβια Γκεστ @olivia.science · 01/03/2025Tired but happy to say this is out w @andreaeyleen.bsky.social: Are Neurocognitive Representations 'Small Cakes'? philsci-archive.pitt.edu/24834/ We analyse cog neuro theories showing how vicious regress, e.g. the homunculus fallacy, is (sadly) alive and well — and importantly how to avoid it. 1/ 2526080 260
Kozzy Voudouris @kozzyvoudouris.bsky.social · 01/03/2025And I forgot to credit Ben Beyret too, who built the original version of Animal-AI from scratch! Thanks for the bump, Matt McGill! 000 0
Kozzy Voudouris @kozzyvoudouris.bsky.social · 01/03/2025You can read the full paper here: rdcu.be/ebLb3 and you can learn how to use Animal-AI here: github.com/Kinds-of-Int...github.comGitHub - Kinds-of-Intelligence-CFI/animal-ai: Animal-AI supports interdisciplinary research to help better understand human, animal, and artificial cognition.Animal-AI supports interdisciplinary research to help better understand human, animal, and artificial cognition. - GitHub - Kinds-of-Intelligence-CFI/animal-ai: Animal-AI supports interdisciplinar... 131 3
Kozzy Voudouris @kozzyvoudouris.bsky.social · 01/03/2025Murray Shanahan, Joel Holmes, Ibrahim Alhas, Ben Slater, Matteo Mecattaf, Wout Schellaert, John Burden, Mati Patel, Niha Chaubey, Niall Donnelly, and many more! We continue to develop the platform and the community, and would love to get your feedback! 111 1
Kozzy Voudouris @kozzyvoudouris.bsky.social · 01/03/2025The Animal-AI Environment is the product of a 7-year research effort and would not have been possible without @lucycheke.bsky.social, @martahalina.bsky.social, Matt McGill, José Hernández-Orallo, 121 2
Kozzy Voudouris @kozzyvoudouris.bsky.social · 01/03/2025You can also use AAI to run tests with humans, through a straightforward game-playing interface. This allows for direct comparison between human and model performance! With AAI, we can accelerate our understanding of both artificial and natural intelligences. 131 3
Kozzy Voudouris @kozzyvoudouris.bsky.social · 01/03/2025AAI has all the tools to replicate tests from comparative cognition, including blocks, ramps, tunnels, buttons, dispensers, and more! We also integrate reinforcement learning libraries so you can test agentic systems like DQN, PPO, and Dreamer-v3, and easily develop your own! 131 3
Kozzy Voudouris @kozzyvoudouris.bsky.social · 01/03/2025AAI was first introduced in 2019, along with the Animal-AI Olympics competition. Since then, we have introduced loads of new features to make AAI faster, more robust, and more useful for interdisciplinary research. 111 1
Kozzy Voudouris @kozzyvoudouris.bsky.social · 01/03/2025In this paper, published online today in Behavior Research Methods, we present the latest version of Animal-AI (AAI). AAI is a virtual 3D environment designed specifically for replicating experimental designs from comparative cognition for use with embodied AI systems. Link: doi.org/10.3758/s134...rdcu.beThe Animal-AI Environment: A virtual laboratory for comparative cognition and artificial intelligence research 131 3
Kozzy Voudouris @kozzyvoudouris.bsky.social · 01/03/2025How can we rigorously investigate the common-sense capabilities of agentic AI systems? How can we build better models of non-human animal cognition? (Re-)introducing the Animal-AI Environment: A virtual laboratory for comparative cognition and artificial intelligence research! 194 9
Reposted by Kozzy VoudourisAndrew Lampinen @lampinen.bsky.social · 28/02/2025New preprint! In arxiv.org/abs/2502.20349 “Naturalistic Computational Cognitive Science: Towards generalizable models and theories that capture the full range of natural behavior” we synthesize AI & cognitive science works to a perspective on seeking generalizable understanding of cognition. Thread:arxiv.orgNaturalistic Computational Cognitive Science: Towards generalizable models and theories that capture the full range of natural behaviorArtificial Intelligence increasingly pursues large, complex models that perform many tasks within increasingly realistic domains. How, if at all, should these developments in AI influence cognitive sc... 17820 78
Reposted by Kozzy VoudourisMirko Thalmann @mirkothm.bsky.social · 28/02/2025Every experience is unique 🌟 light shifts, angles change, yet we recognize objects effortlessly. How do our minds do this? And (how) do they differ from machines? In our new preprint with @ericschulz.bsky.social, we review human generalization and compare it to machine generalization: osf.io/k6ect 087 8
Reposted by Kozzy VoudourisMilena Rmus @milenamr7.bsky.social · 26/02/2025About a month late posting this, but here's a new project with @ericschulz.bsky.social, @akjagadish.bsky.social, @marvinmathony.bsky.social and Tobias Ludwig We are using LLMs to propose cognitive models in learning and decision making data. Presenting this work at RLDM! arxiv.org/abs/2502.00879arxiv.orgTowards Automation of Cognitive Modeling using Large Language ModelsComputational cognitive models, which formalize theories of cognition, enable researchers to quantify cognitive processes and arbitrate between competing theories by fitting models to behavioral data.... 0218 21
Reposted by Kozzy Voudourislucaschubu.bsky.social @lucaschubu.bsky.social · 25/02/2025In previous work we found that VLMs fall short of human visual cognition. To make them better, we fine-tuned them on visual cognition tasks. We find that while this improves performance on the fine-tuning task, it does not lead to models that generalize to other related tasks: 195 9
