paper-with-me

Papers

Active Inference in Robotics and Artificial Agents: Survey and Challenges

2021-12-03 · Pablo Lanillos, Cristian Meo, Corrado Pezzato, Ajith Anil Meera, Mohamed Baioumy, Wataru Ohata, Alexander Tschantz, Beren Millidge, Martijn Wisse, Christopher L. Buckley, Jun Tani

Active inference is a mathematical framework which originated in computational neuroscience as a theory of how the brain implements action, perception and learning. Recently, it has been shown to be a promising approach to the problems of state-estimation and control under uncertainty, as well as a foundation for the construction of goal-driven behaviours in robotics and artificial agents in general. Here, we review the state-of-the-art theory and implementations of active inference for state-estimation, control, planning and learning; describing current achievements with a particular focus on robotics. We showcase relevant experiments that illustrate its potential in terms of adaptation, generalization and robustness. Furthermore, we connect this approach with other frameworks and discuss its expected benefits and challenges: a unified framework with functional biological plausibility using variational Bayesian inference.

📄 PDF Abstract BibTeX arXiv:2112.01871

Code (0)

등록된 구현이 없습니다.

Tasks

Bayesian InferenceState EstimationSurvey

Similar Papers 제목 키워드 기반

Sensorimotor representation learning for an "active self" in robots: A model survey

2020-11-25 · Phuong D. H. Nguyen, Yasmin Kim Georgie, Ezgi Kayhan, Manfred Eppe 외

Safe human-robot interactions require robots to be able to learn how to behave appropriately in \sout{humans' world} \rev{spaces populated by people} and thus to cope with the challenges posed by our dynamic and unstruct…

Representation Learning

The Free Energy Principle for Perception and Action: A Deep Learning Perspective

2022-07-13 · Pietro Mazzaglia, Tim Verbelen, Ozan Çatal, Bart Dhoedt

The free energy principle, and its corollary active inference, constitute a bio-inspired theory that assumes biological agents act to remain in a restricted set of preferred states of the world, i.e., they minimize their…

Deep LearningVariational Inference

Understanding Tool Discovery and Tool Innovation Using Active Inference

2023-11-07 · Poppy Collis, Paul F Kinghorn, Christopher L Buckley

The ability to invent new tools has been identified as an important facet of our ability as a species to problem solve in dynamic and novel environments. While the use of tools by artificial agents presents a challenging…

Understanding the Application of Utility Theory in Robotics and Artificial Intelligence: A Survey

2023-06-15 · Qin Yang, Rui Liu

As a unifying concept in economics, game theory, and operations research, even in the Robotics and AI field, the utility is used to evaluate the level of individual needs, preferences, and interests. Especially for decis…

Decision Making

"Dave...I can assure you...that it's going to be all right..." -- A definition, case for, and survey of algorithmic assurances in human-autonomy trust relationships

2017-11-08 · Brett W. Israelsen, Nisar R. Ahmed

People who design, use, and are affected by autonomous artificially intelligent agents want to be able to \emph{trust} such agents -- that is, to know that these agents will perform correctly, to understand the reasoning…

All