Cover Image

Active Inference and Reinforcement Learning: A unified inference on continuous state and action spaces under partial observability

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Malekzadeh, Parvin, Plataniotis, Konstantinos N.
Format:	Preprint
Published:	2022
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A unified uncertainty-aware exploration: Combining epistemic and aleatory uncertainty
by: Malekzadeh, Parvin, et al.
Published: (2024)

A Robust Quantile Huber Loss With Interpretable Parameter Adjustment In Distributional Reinforcement Learning
by: Malekzadeh, Parvin, et al.
Published: (2024)

Uncertainty-aware transfer across tasks using hybrid model-based successor feature reinforcement learning
by: Malekzadeh, Parvin, et al.
Published: (2023)

EX-DRL: Hedging Against Heavy Losses with EXtreme Distributional Reinforcement Learning
by: Malekzadeh, Parvin, et al.
Published: (2024)

Active inference for action-unaware agents
by: Torresan, Filippo, et al.
Published: (2025)

GSTAM: Efficient Graph Distillation with Structural Attention-Matching
by: Rasti-Meymandi, Arash, et al.
Published: (2024)

Forager: a lightweight testbed for continual learning with partial observability in RL
by: Tang, Steven, et al.
Published: (2026)

Constrained latent state modeling: A unifying perspective on representation learning under competing constraints
by: Quellec, Gwenolé
Published: (2026)

Value of Information-Enhanced Exploration in Bootstrapped DQN
by: Plataniotis, Stergios, et al.
Published: (2025)

Learning in complex action spaces without policy gradients
by: Tavakoli, Arash, et al.
Published: (2024)

Normalized Conditional Mutual Information Surrogate Loss for Deep Neural Classifiers
by: Ye, Linfeng, et al.
Published: (2026)

CLEF: Clinically-Guided Contrastive Learning for Electrocardiogram Foundation Models
by: Shu, Yuxuan, et al.
Published: (2025)

Amortized Active Causal Induction with Deep Reinforcement Learning
by: Annadani, Yashas, et al.
Published: (2024)

Sample Efficient Active Algorithms for Offline Reinforcement Learning
by: Roy, Soumyadeep, et al.
Published: (2026)

SAFE-RL: Saliency-Aware Counterfactual Explainer for Deep Reinforcement Learning Policies
by: Samadi, Amir, et al.
Published: (2024)

Using Part-based Representations for Explainable Deep Reinforcement Learning
by: Kirtas, Manos, et al.
Published: (2024)

Predicting partially observable dynamical systems via diffusion models with a multiscale inference scheme
by: Morel, Rudy, et al.
Published: (2025)

Complex behavior from intrinsic motivation to occupy action-state path space
by: Ramírez-Ruiz, Jorge, et al.
Published: (2022)

Enabling Realtime Reinforcement Learning at Scale with Staggered Asynchronous Inference
by: Riemer, Matthew, et al.
Published: (2024)

Demonstrating the Continual Learning Capabilities and Practical Application of Discrete-Time Active Inference
by: Prakki, Rithvik
Published: (2024)

Reinforcement Learning in hyperbolic space for multi-step reasoning
by: Xu, Tao, et al.
Published: (2025)

Combining Bayesian Inference and Reinforcement Learning for Agent Decision Making: A Review
by: Zhou, Chengmin, et al.
Published: (2025)

Active Asymmetric Multi-Agent Multimodal Learning under Uncertainty
by: Liu, Rui, et al.
Published: (2026)

Robust Federated Learning under Adversarial Attacks via Loss-Based Client Clustering
by: Kritharakis, Emmanouil, et al.
Published: (2025)

Reinforcement learning with combinatorial actions for coupled restless bandits
by: Xu, Lily, et al.
Published: (2025)

Real-World Reinforcement Learning of Active Perception Behaviors
by: Hu, Edward S., et al.
Published: (2025)

Prioritize Alignment in Dataset Distillation
by: Li, Zekai, et al.
Published: (2024)

Inference-Time Alignment Control for Diffusion Models with Reinforcement Learning Guidance
by: Jin, Luozhijie, et al.
Published: (2025)

Bounding-Box Inference for Error-Aware Model-Based Reinforcement Learning
by: Talvitie, Erin J., et al.
Published: (2024)

Beyond Inference-Time Search: Reinforcement Learning Synthesizes Reusable Solvers
by: Massoudi, Soheyl, et al.
Published: (2026)

CIER: A Novel Experience Replay Approach with Causal Inference in Deep Reinforcement Learning
by: Wang, Jingwen, et al.
Published: (2024)

FedD2S: Personalized Data-Free Federated Knowledge Distillation
by: Atapour, Kawa, et al.
Published: (2024)

APRIL: Active Partial Rollouts in Reinforcement Learning to Tame Long-tail Generation
by: Zhou, Yuzhen, et al.
Published: (2025)

Deep Belief Markov Models for POMDP Inference
by: Arcieri, Giacomo, et al.
Published: (2025)

Generalizing soft actor-critic algorithms to discrete action spaces
by: Zhang, Le, et al.
Published: (2024)

Application of linear regression and quasi-Newton methods to the deep reinforcement learning in continuous action cases
by: Komatsu, Hisato
Published: (2025)

SAS: Semantic-aware Sampling for Generative Dataset Distillation
by: Li, Mingzhuo, et al.
Published: (2026)

Value of Information and Reward Specification in Active Inference and POMDPs
by: Wei, Ran
Published: (2024)

Active Inference with Reusable State-Dependent Value Profiles
by: Poschl, Jacob
Published: (2025)

Constructive Symbolic Reinforcement Learning via Intuitionistic Logic and Goal-Chaining Inference
by: Patrascu, Andrei T.
Published: (2025)