mlsanityData to 7 Oct 2026

Active Inference in Robotics and Artificial Agents: Survey and Challenges

arXiv 2112.01871 ↗First posted 3 Dec 2021cs.RO cs.AI cs.LGcited by 52

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Abstract (arXiv)

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.

Key facts. Cited by 52 papers in the map (data through 7 Oct 2026). Builds on 48 of its 122 references that are in the map. First posted on arXiv 3 Dec 2021.

Builds on

48 of 122 references.

References · 48

  1. 2018Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actorcited by 4,635
  2. 2018Reinforcement Learning and Control as Probabilistic Inference: Tutorial and Reviewcited by 466
  3. 2015A Recurrent Latent Variable Model for Sequential Datacited by 362
  4. 2020Active inference on discrete state-spaces: a synthesiscited by 91
  5. 2020Deep active inference agents using Monte-Carlo methodscited by 72
  6. 2017The free energy principle for action and perception: A mathematical reviewcited by 66
  7. 2020Sophisticated Inferencecited by 56
  8. 2019Deep Active Inference as Variational Policy Gradientscited by 52
  9. 2020Reinforcement Learning through Active Inferencecited by 47
  10. 2017Deep Active Inferencecited by 44
  11. 2020On the Relationship Between Active Inference and Control as Inferencecited by 42
  12. 2020Whence the Expected Free Energy?cited by 40
36 more
  1. 2019Variational Inference MPC for Bayesian Model-based Reinforcement Learningcited by 39
  2. 2019Scaling active inferencecited by 30
  3. 2019End-to-End Pixel-Based Deep Active Inference for Body Perception and Actioncited by 24
  4. 2020Active Inference and Behavior Trees for Reactive Action Planning and Execution in Roboticscited by 23
  5. 2021Multimodal VAE Active Inference Controllercited by 21
  6. 2021Contrastive Active Inferencecited by 21
  7. 2020Deep Active Inference for Partially Observable MDPscited by 20
  8. 2019Stochastic Optimal Control as Approximate Input Inferencecited by 14
  9. 2018Adaptive robot body learning and estimation through predictive codingcited by 13
  10. 2021Predictive Processing in Cognitive Robotics: a Reviewcited by 13
  11. 2019Bayesian policy selection using active inferencecited by 12
  12. 2020Robot self/other distinction: active inference meets neural networks learning in a mirrorcited by 12
  13. 2019A Novel Adaptive Controller for Robot Manipulators based on Active Inferencecited by 11
  14. 2021Understanding the Origin of Information-Seeking Exploration in Probabilistic Objectives for Controlcited by 10
  15. 2020Active Inference for Integrated State-Estimation, Control, and Learningcited by 9
  16. 2020Active Inference or Control as Inference? A Unifying Viewcited by 9
  17. 2020Deep Active Inference for Autonomous Robot Navigationcited by 8
  18. 2020A deep active inference model of the rubber-hand illusioncited by 7
  19. 2017An active inference implementation of phototaxiscited by 6
  20. 2021Free Energy Principle for State and Input Estimation of a Quadcopter Flying in Windcited by 6
  21. 2019Application of the Free Energy Principle to Estimation and Controlcited by 5
  22. 2020Goal-Directed Planning for Habituated Agents by Active Inference Using a Variational Recurrent Neural Networkcited by 5
  23. 2020Robot in the mirror: toward an embodied computational model of mirror self-recognitioncited by 5
  24. 2021Leading or Following? Dyadic Robot Imitative Interaction Using the Active Inference Frameworkcited by 5
  25. 2021Fault-tolerant Control of Robot Manipulators with Sensory Faults using Unbiased Active Inferencecited by 5
  26. 2021Neuroscience-inspired perception-action in robotics: applying active inference for state estimation, control and self-perceptioncited by 5
  27. 2020On Kalman-Bucy filters, linear quadratic control and active inferencecited by 4
  28. 2018Drifting perceptual patterns suggest prediction errors fusion rather than hypothesis selection: replicating the rubber-hand illusion on a robotcited by 3
  29. 2019Cognitive and motor compliance in intentional human-robot interactioncited by 3
  30. 2020Reinforcement Learning as Iterative and Amortised Inferencecited by 3
  31. 2021Online reinforcement learning with sparse rewards through an active inference capsulecited by 3
  32. 2021Towards Stochastic Fault-tolerant Control using Precision Learning and Active Inferencecited by 3
  33. 2021Goal-Directed Planning by Reinforcement Learning and Active Inferencecited by 2
  34. 2021Deep Active Inference for Pixel-Based Discrete Control: Evaluation on the Car Racing Problemcited by 2
  35. 2021A Brain Inspired Learning Algorithm for the Perception of a Quadrotor in Windcited by 2
  36. 2021Robot Localization and Navigation through Predictive Processing using LiDARcited by 1

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 10; 2023: 12; 2024: 16; 2025: 8; 2026: 6.

52 papers.

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  1. 2022Predictive Coding: Towards a Future of Deep Learning beyond Backpropagation?cited by 45
  2. 2023Neither hype nor gloom do DNNs justicecited by 40
  3. 2023World Models and Predictive Coding for Cognitive and Developmental Robotics: Frontiers and Challengescited by 35
  4. 2023Brain-inspired Computational Intelligence via Predictive Codingcited by 30
  5. 2022The Free Energy Principle for Perception and Action: A Deep Learning Perspectivecited by 24
  6. 2024Active Inference as a Model of Agencycited by 12
  7. 2023Hierarchical generative modelling for autonomous robotscited by 9
  8. 2022Object-based active inferencecited by 7
  9. 2022Interactive inference: a multi-agent model of cooperative joint actionscited by 7
  10. 2024Predictive Coding Networks and Inference Learning: Tutorial and Surveycited by 7
  11. 2024Masked Generative Priors Improve World Models Sequence Modelling Capabilitiescited by 7
  12. 2022Disentangling Shape and Pose for Object-Centric Deep Active Inference Modelscited by 6
38 more
  1. 2022Active Inference for Autonomous Decision-Making with Contextual Multi-Armed Banditscited by 6
  2. 2023Resolving uncertainty on the fly: Modeling adaptive driving behavior as active inferencecited by 6
  3. 2022Geometric Methods for Sampling, Optimisation, Inference and Adaptive Agentscited by 5
  4. 2024Value of Information and Reward Specification in Active Inference and POMDPscited by 4
  5. 2022Learning Policies for Continuous Control via Transition Modelscited by 3
  6. 2023Observation-Augmented Contextual Multi-Armed Bandits for Robotic Search and Explorationcited by 3
  7. 2024Possible Principles for Aligned Structure Learning Agentscited by 3
  8. 2025Deep Active Inference Agents for Delayed and Long-Horizon Environmentscited by 3
  9. 2022Active Exploration based on Information Gain by Particle Filter for Efficient Spatial Concept Formationcited by 2
  10. 2023Object-Centric Scene Representations using Active Inferencecited by 2
  11. 2023Adaptive Noise Covariance Estimation under Colored Noise using Dynamic Expectation Maximizationcited by 2
  12. 2024Confidence-Aware Decision-Making and Control for Tool Selectioncited by 2
  13. 2024Object-centric proto-symbolic behavioural reasoning from pixelscited by 2
  14. 2025Free Energy Risk Metrics for Systemically Safe AI: Gatekeeping Multi-Agent Studycited by 2
  15. 2025EASE: Embodied Active Event Perception via Self-Supervised Energy Minimizationcited by 2
  16. 2022Deriving time-averaged active inference from control principlescited by 1
  17. 2023Beyond the limitations of any imaginable mechanism: large language models and psycholinguisticscited by 1
  18. 2023Grid-SD2E: A General Grid-Feedback in a System for Cognitive Learningcited by 1
  19. 2023Modeling arousal potential of epistemic emotions using Bayesian information gain: Inquiry cycle driven by free energy fluctuationscited by 1
  20. 2024Active Inference Meeting Energy-Efficient Control of Parallel and Identical Machinescited by 1
  21. 2024Toward Universal and Interpretable World Models for Open-ended Learning Agentscited by 1
  22. 2024Coupled autoregressive active inference agents for control of multi-joint dynamical systemscited by 1
  23. 2024Free Energy Projective Simulation (FEPS): Active inference with interpretabilitycited by 1
  24. 2024Context-Based Echo State Networks with Prediction Confidence for Human-Robot Shared Controlcited by 1
  25. 2025Active Inference for Energy Control and Planning in Smart Buildings and Communitiescited by 1
  26. 2025Designing Tools with Control Confidencecited by 1
  27. 2023Fixing the problems of deep neural networks will require better training data and learning algorithmscited by 0
  28. 2024Dynamic planning in hierarchical active inferencecited by 0
  29. 2024Seeing Through Uncertainty: Free-Energy-Inspired Real-Time Adaptation for Robust Visual Navigationcited by 0
  30. 2024Online Pareto-Optimal Decision-Making for Complex Tasks using Active Inferencecited by 0
  31. 2024Environment-Centric Active Inferencecited by 0
  32. 2025Spiking Neural Networks for Continuous Control via End-to-End Model-Based Learningcited by 0
  33. 2025Natural Building Blocks for Structured World Models: Theory, Evidence, and Scalingcited by 0
  34. 2025Prior preferences in active inference agents: soft, hard, and goal shapingcited by 0
  35. 2026Distributional Active Inferencecited by 0
  36. 2026Active Inference for Micro-Gesture Recognition: EFE-Guided Temporal Sampling and Adaptive Learningcited by 0
  37. 2026Active Inference for Adaptive Traffic Signal Control in Noisy Nonstationary IoT Environmentscited by 0
  38. 2026A Hardware-oriented Approach for Efficient Bayesian Inference Computation and Deploymentcited by 0

50 most cited of 52 All 52 (JSON)