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

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The underlying processes that enable self-perception are crucial for understanding multisensory integration, body perception and action, and the development of the self. Previous computational models have overlooked an essential aspect:…

神经元与认知 · 定量生物学 2022-08-30 Jonathan Bauermeister , Pablo Lanillos

Infants often exhibit goal-directed behaviors, such as reaching for a sensory stimulus, even when no external reward criterion is provided. These intrinsically motivated behaviors facilitate spontaneous exploration and learning of the body…

人工智能 · 计算机科学 2025-11-12 Dongmin Kim , Hoshinori Kanazawa , Naoto Yoshida , Yasuo Kuniyoshi

Self/other distinction and self-recognition are important skills for interacting with the world, as it allows humans to differentiate own actions from others and be self-aware. However, only a selected group of animals, mainly high order…

机器人学 · 计算机科学 2020-04-14 Pablo Lanillos , Jordi Pages , Gordon Cheng

Self-recognition or self-awareness is a capacity attributed typically only to humans and few other species. The definitions of these concepts vary and little is known about the mechanisms behind them. However, there is a Turing test-like…

机器人学 · 计算机科学 2021-02-08 Matej Hoffmann , Shengzhi Wang , Vojtech Outrata , Elisabet Alzueta , Pablo Lanillos

With resurgent interest in individual differences in perception, cognition and behavioural control, as early indicators of disease, endophenotypes, or a means to relate brain structure to function, behavioural tasks are increasingly being…

神经元与认知 · 定量生物学 2013-09-16 Frederic Boy , Petroc Sumner

Current literature holds that many cognitive functions can be performed outside consciousness. Evidence for this view comes from unconscious priming. In a typical experiment, visual stimuli are masked, such that participants are close to…

应用统计 · 统计学 2021-06-08 Sascha Meyen , Iris A. Zerweck , Catarina Amado , Ulrike von Luxburg , Volker H. Franz

Background: Exploration of the physical environment is an indispensable precursor to information acquisition and knowledge consolidation for living organisms. Yet, current artificial intelligence models lack these autonomy capabilities…

人工智能 · 计算机科学 2025-09-10 Gustavo Assunção , Miguel Castelo-Branco , Paulo Menezes

Active inference is a first principle account of how autonomous agents operate in dynamic, non-stationary environments. This problem is also considered in reinforcement learning (RL), but limited work exists on comparing the two approaches…

人工智能 · 计算机科学 2021-02-15 Noor Sajid , Philip J. Ball , Thomas Parr , Karl J. Friston

Active inference is a unifying theory for perception and action resting upon the idea that the brain maintains an internal model of the world by minimizing free energy. From a behavioral perspective, active inference agents can be seen as…

机器学习 · 计算机科学 2024-01-17 Pietro Mazzaglia , Tim Verbelen , Bart Dhoedt

Obtaining reliable feedback from the environment is a fundamental capability for intelligent agents to evaluate the correctness of their actions and to accumulate reusable knowledge. However, most existing approaches rely on predefined…

人工智能 · 计算机科学 2026-01-09 Hong Su

Inspired by the remarkable ability of the infant visual learning system, a recent study collected first-person images from children to analyze the `training data' that they receive. We conduct a follow-up study that investigates two…

计算机视觉与模式识别 · 计算机科学 2019-06-05 Satoshi Tsutsui , Dian Zhi , Md Alimoor Reza , David Crandall , Chen Yu

The active inference framework (AIF) is a promising new computational framework grounded in contemporary neuroscience that can produce human-like behavior through reward-based learning. In this study, we test the ability for the AIF to…

神经元与认知 · 定量生物学 2022-11-21 Zhizhuo Yang , Gabriel J. Diaz , Brett R. Fajen , Reynold Bailey , Alexander Ororbia

Providing artificial agents with the same computational models of biological systems is a way to understand how intelligent behaviours may emerge. We present an active inference body perception and action model working for the first time in…

机器人学 · 计算机科学 2021-02-08 Guillermo Oliver , Pablo Lanillos , Gordon Cheng

Active inference is a formal approach to study cognition based on the notion that adaptive agents can be seen as engaging in a process of approximate Bayesian inference, via the minimisation of variational and expected free energies.…

人工智能 · 计算机科学 2025-08-19 Filippo Torresan , Keisuke Suzuki , Ryota Kanai , Manuel Baltieri

Recent advances in theoretical biology suggest that basal cognition and sentient behaviour are emergent properties of in vitro cell cultures and neuronal networks, respectively. Such neuronal networks spontaneously learn structured…

Robotic manipulation stands as a largely unsolved problem despite significant advances in robotics and machine learning in the last decades. One of the central challenges of manipulation is partial observability, as the agent usually does…

机器人学 · 计算机科学 2022-06-22 Tim Schneider , Boris Belousov , Hany Abdulsamad , Jan Peters

Active inference is an ambitious theory that treats perception, inference and action selection of autonomous agents under the heading of a single principle. It suggests biologically plausible explanations for many cognitive phenomena,…

人工智能 · 计算机科学 2018-06-22 Martin Biehl , Christian Guckelsberger , Christoph Salge , Simón C. Smith , Daniel Polani

Joint improvisation is observed to emerge spontaneously among humans performing joint action tasks, and has been associated with high levels of movement synchrony and enhanced sense of social bonding. Exploring the underlying cognitive and…

The mirror neuron theory that has enjoyed continued validations was developed with no particular attention to the phenomenon of the vision. Understandably the perception of vision has always been thought to happen, naturally, as that for…

神经元与认知 · 定量生物学 2022-03-01 Jahan N. Schad

Positive affect has been linked to increased interest, curiosity and satisfaction in human learning. In reinforcement learning, extrinsic rewards are often sparse and difficult to define, intrinsically motivated learning can help address…

计算机视觉与模式识别 · 计算机科学 2021-04-06 Dean Zadok , Daniel McDuff , Ashish Kapoor
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