相关论文: Active Inference with a Self-Prior in the Mirror-M…

We investigate inferring individual preferences and the contradiction of individual preferences with group preferences through direct measurement of the brain. We report an experiment where brain activity collected from 31 participants…

An experimental unit is an opportunity to randomly apply or withhold a treatment. There is interference between units if the application of the treatment to one unit may also affect other units. In cognitive neuroscience, a common form of…

Active visual exploration aims to assist an agent with a limited field of view to understand its environment based on partial observations made by choosing the best viewing directions in the scene. Recent methods have tried to address this…

Unlike robots, humans learn, adapt and perceive their bodies by interacting with the world. Discovering how the brain represents the body and generates actions is of major importance for robotics and artificial intelligence. Here we discuss…

Self-awareness is a critical factor in social human-human interaction and, hence, in social HCI interaction. Increasing self-awareness through mirrors or video recordings is common in face-to-face trainings, since it influences antecedents…

Active inference is a normative principle underwriting perception, action, planning, decision-making and learning in biological or artificial agents. From its inception, its associated process theory has grown to incorporate complex…

This paper introduces a new form of real-time affective interface that engages the user in a process of conceptualisation of their emotional state. Inspired by Barrett's Theory of Constructed Emotion, `Mirror Ritual' aims to expand upon the…

Measuring the statistical dependence between observed signals is a primary tool for scientific discovery. However, biological systems often exhibit complex non-linear interactions that currently cannot be captured without a priori knowledge…

We seek to clarify the concept of active inference by disentangling it from the Free Energy Principle. We show how the optimizations that need to be carried out in order to implement active inference in discrete state spaces can be…

The purpose of this study was to investigate the relationship between preschoolers' cognitive abilities and their fairness-related allocation behaviors in a dilemma of equity-efficiency conflict. Four- to 6-year-olds in Experiment 1 (N =…

Active inference is a mathematical framework for understanding how agents (biological or artificial) interact with their environments, enabling continual adaptation and decision-making. It combines Bayesian inference and free energy…

Large amounts of labeled training data are one of the main contributors to the great success that deep models have achieved in the past. Label acquisition for tasks other than benchmarks can pose a challenge due to requirements of both…

During interaction with others, we perceive and produce social actions in close temporal distance or even simultaneously. It has been argued that the motor system is involved in perception and action, playing a fundamental role in the…

Predicting the behaviors of other road users is crucial to safe and intelligent decision-making for autonomous vehicles (AVs). However, most motion prediction models ignore the influence of the AV's actions and the planning module has to…

Naturalistic fMRI has been suggested to be a powerful alternative for investigations of human brain function. Stimulus-induced activation has been playing an essential role in fMRI-based brain function analyses. Due to the complexity of the…

The way the brain selects and controls actions is still widely debated. Mainstream approaches based on Optimal Control focus on stimulus-response mappings that optimize cost functions. Ideomotor theory and cybernetics propose a different…

Learning useful representations with little or no supervision is a key challenge in artificial intelligence. We provide an in-depth review of recent advances in representation learning with a focus on autoencoder-based models. To organize…

Flexible, goal-directed behavior is a fundamental aspect of human life. Based on the free energy minimization principle, the theory of active inference formalizes the generation of such behavior from a computational neuroscience…

Efficient exploration is a long-standing problem in reinforcement learning since extrinsic rewards are usually sparse or missing. A popular solution to this issue is to feed an agent with novelty signals as intrinsic rewards. In this work,…

In cognitive neuroscience the sense of agency is defined as the as the experience of controlling ones own actions and, through this control, affecting the external world. At CHI 2012 I presented a paper entitled I did that! Measuring Users…