In praise of folly: flexible goals and human cognition

J Chu, JB Tenenbaum, LE Schulz - Trends in Cognitive Sciences, 2024 - cell.com
Humans often pursue idiosyncratic goals that appear remote from functional ends, including
information gain. We suggest that this is valuable because goals (even prima facie foolish or …

[HTML][HTML] Designing for motivation, engagement and wellbeing in digital experience

D Peters, RA Calvo, RM Ryan - Frontiers in psychology, 2018 - frontiersin.org
Research in psychology has shown that both motivation and wellbeing are contingent on the
satisfaction of certain psychological needs. Yet, despite a long-standing pursuit in human …

[HTML][HTML] Meta-learning, social cognition and consciousness in brains and machines

A Langdon, M Botvinick, H Nakahara, K Tanaka… - Neural Networks, 2022 - Elsevier
The intersection between neuroscience and artificial intelligence (AI) research has created
synergistic effects in both fields. While neuroscientific discoveries have inspired the …

Supporting human autonomy in AI systems: A framework for ethical enquiry

RA Calvo, D Peters, K Vold, RM Ryan - Ethics of digital well-being: A …, 2020 - Springer
Autonomy has been central to moral and political philosophy for millennia, and has been
positioned as a critical aspect of both justice and wellbeing. Research in psychology …

Goals as reward-producing programs

G Davidson, G Todd, J Togelius, TM Gureckis… - Nature Machine …, 2025 - nature.com
People are remarkably capable of generating their own goals, beginning with child's play
and continuing into adulthood. Despite considerable empirical and computational work on …

Exploration in neo-Hebbian reinforcement learning: Computational approaches to the exploration–exploitation balance with bio-inspired neural networks

A Triche, AS Maida, A Kumar - Neural Networks, 2022 - Elsevier
Recent theoretical and experimental works have connected Hebbian plasticity with the
reinforcement learning (RL) paradigm, producing a class of trial-and-error learning in …

Adversarial intrinsic motivation for reinforcement learning

I Durugkar, M Tec, S Niekum… - Advances in Neural …, 2021 - proceedings.neurips.cc
Learning with an objective to minimize the mismatch with a reference distribution has been
shown to be useful for generative modeling and imitation learning. In this paper, we …

Curiosity‐based learning in infants: A neurocomputational approach

KE Twomey, G Westermann - Developmental science, 2018 - Wiley Online Library
Infants are curious learners who drive their own cognitive development by imposing
structure on their learning environment as they explore. Understanding the mechanisms by …

[КНИГА][B] The effective and ethical development of artificial intelligence: an opportunity to improve our wellbeing

T Walsh, N Levy, G Bell, A Elliott, J Maclaurin, I Mareels… - 2019 - researchers.mq.edu.au
Artificial Intelligence Page 1 The effective and ethical development of artificial intelligence: An
opportunity to improve our wellbeing. Report for the Australian Council of Learned Academies …

Cognitive and metacognitive, motivational, and resource considerations for learning new skills across the lifespan

P Sheffler, TM Rodriguez… - Wiley Interdisciplinary …, 2022 - Wiley Online Library
Across the lifespan, learners have to tackle the challenges of learning new skills. These
skills can range from abilities needed for survival, such as learning languages, learning to …