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Found 12 papers, 2 papers with code
Transitive inference as probabilistic preference learning
We propose a novel framework that casts TI as a probabilistic preference learning task, using one-parameter Mallows models.
Neural representation in active inference: using generative models to interact with -- and understand -- the lived world
This paper considers neural representation through the lens of active inference, a normative framework for understanding brain function.
Modeling motor control in continuous-time Active Inference: a survey
This article provides a technical illustration of Active Inference models in continuous time and a brief survey of Active Inference models that solve four kinds of control problems; namely, the control of goal-directed reaching movements, active sensing, the resolution of multisensory conflict during movement and the integration of decision-making and motor control.
Bridging Cognitive Maps: a Hierarchical Active Inference Model of Spatial Alternation Tasks and the Hippocampal-Prefrontal Circuit
Through a series of simulations, we demonstrate that the model's dual layers acquire effective cognitive maps for navigation within physical (HC map) and task (mPFC map) spaces, using a biologically-inspired approach: a clone-structured cognitive graph.
Integrating cognitive map learning and active inference for planning in ambiguous environments
Living organisms need to acquire both cognitive maps for learning the structure of the world and planning mechanisms able to deal with the challenges of navigating ambiguous environments.
Integrating large language models and active inference to understand eye movements in reading and dyslexia
We present a novel computational model employing hierarchical active inference to simulate reading and eye movements.
World Models and Predictive Coding for Cognitive and Developmental Robotics: Frontiers and Challenges
Therefore, in this paper, we clarify the definitions, relationships, and status of current research on these topics, as well as missing pieces of world models and predictive coding in conjunction with crucially related concepts such as the free-energy principle and active inference in the context of cognitive and developmental robotics.
Interactive inference: a multi-agent model of cooperative joint actions
These simulations illustrate that interactive inference supports successful multi-agent joint actions and reproduces key cognitive and behavioral dynamics of "leaderless" and "leader-follower" joint actions observed in human-human experiments.
Information-theoretical analysis of the neural code for decoupled face representation
Processing faces accurately and efficiently is a key capability of humans and other animals that engage in sophisticated social tasks.
Skilled motor control implies a low entropy of states but a high entropy of actions
The mastery of skills such as playing tennis or balancing an inverted pendulum implies a very accurate control of movements to achieve the task goals.
Active Inference Tree Search in Large POMDPs
Here, we introduce a novel method to plan in POMDPs--Active Inference Tree Search (AcT)--that combines the normative character and biological realism of a leading planning theory in neuroscience (Active Inference) and the scalability of tree search methods in AI.
Moral decisions in the age of COVID-19: your choices really matter
The moral decisions we make during this period, such as deciding whether to comply with quarantine rules, have unprecedented societal effects.
Computers and Society Populations and Evolution
