Program at a Glance


Thursday

Session 1: Developmental mechanisms and exploration

  • 2-2:40pm: Cate Hartley + Michael Littman – [TBD – developmental mechanisms in both natural and artificial intelligence]
  • 2:40-3:20pm: Andreas Krause – Uncertainty-guided Exploration in Model-based Deep Reinforcement Learning
  • 3:20-4:00pm: Malcolm MacIver – The Geological Basis of Intelligence

Friday

Session 2: Uncertainty and exploration  

  • 9-9:40am: Claire Vernade – Partially Observable Reinforcement Learning with Memory Traces
  • 9:40-10am: Kelly Zhang et al. – Informed Exploration via Autoregressive Generation
  • 10-10:20am: Janne Reynders et al. – Cognitive mechanisms of strategic variability in stable, volatile, and adversarial environments
  • 10:20-11:00am: Romy Froemer – Attention in value-based choice: Active and passive uncertainty reduction mechanisms

Session 3: Multi-agent interaction

  • 11:30-12:10pm: Karl Tuyls – The Role of Empirical Game Theory for Learning Agents
  • 12:10-12:30pm: Sonja Johnson-Yu et al. – Investigating active electrosensing and communication in deep-reinforcement learning trained artificial fish collectives
  • 12:30-1:10 pm: Amanda Prorok – Synthesizing Diverse Policies for Multi-Robot Coordination

Session 4: Modeling the world and state representations

  • 2-2:40pm: Tim Rocktaeschel – Open-Endedness and World Models
  • 2:40-3pm: Matthew Barker et al. – Translating Latent State World Model Representations into Natural Language
  • 3-3:20pm: Jasmine Stone – A model of distributed reinforcement learning systems inspired by the Drosophila mushroom body 
  • 3:20-4pm: Angela Radulescu – Attention and affect in human RLDM: insights from computational psychiatry

Saturday

Session 5: Agency, habits, and biases

  • 9-9:40am: Sanne de Wit – Investigating Habit Making and Breaking in Real-World Settings
  • 9:40-10am: Kelly Donegan et al. – Compulsivity is associated with an increase in stimulus-response habit learning
  • 10am-10:20am: Carlos Brito et al. – Hierarchical Integration of RL and Cerebellar Control for Robust Flexible Locomotion
  • 10:20-10:40am: Sabrina Abram et al. – Agency in action selection and action execution produce distinct biases in decision making
  • 10:40-11am: David Abel et al. – Agency is Frame-Dependent

Session 6: Multi-agent interaction and decision making

  • 11:30-12:10pm: Weinan Zhang – Large Language Models Based Multi-Agent Intelligence: The Progress So Far
  • 12:10-12:30pm: Jordan Lei et al. – Choice and Deliberation in a Strategic Planning Game in Monkeys
  • 12:30-1:10pm: Valentin Wyart – Alternatives to exploration? Moving up and down the ladder of causation in humans

Session 7: Foundations of RL in algorithms and in neural signals

  • 2-2:40pm: Doina Precup – (update title)
  • 2:40-3:00pm: Michael Bowling et al. – Rethinking the Foundations for Continual Reinforcement Learning
  • 3:00-3:40pm: Nicolas Tritsch – Defining timescales of neuromodulation by dopamine
  • 3:40-4:00pm: Margarida Sousa et al. – Learning distributional predictive maps for fast risk-adaptive control

Session 8: Planning 

  • 4:30-4:50pm: Sixing Chen et al. – Meta-learning of human-like planning strategies
  • 4:50-5:30pm: Wei Ji Ma – Human planning and memory in combinatorial games
  • 5:30-5:40pm: Final words