Cover Image

Ontology-Enhanced Decision-Making for Autonomous Agents in Dynamic and Partially Observable Environments

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Ghanadbashi, Saeedeh, Golpayegani, Fatemeh
Format:	Preprint
Published:	2024
Subjects:	Artificial Intelligence Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

PIANIST: Learning Partially Observable World Models with LLMs for Multi-Agent Decision Making
by: Light, Jonathan, et al.
Published: (2024)

Transformer-Based Reinforcement Learning for Autonomous Orbital Collision Avoidance in Partially Observable Environments
by: Georges, Thomas, et al.
Published: (2026)

An Empirical Study on the Power of Future Prediction in Partially Observable Environments
by: Kwon, Jeongyeol, et al.
Published: (2024)

Temporal Knowledge-Graph Memory in a Partially Observable Environment
by: Kim, Taewoon, et al.
Published: (2024)

Mitigating Partial Observability in Sequential Decision Processes via the Lambda Discrepancy
by: Allen, Cameron, et al.
Published: (2024)

Online Feedback Efficient Active Target Discovery in Partially Observable Environments
by: Sarkar, Anindya, et al.
Published: (2025)

Robust Decision Making with Partially Calibrated Forecasts
by: Kiyani, Shayan, et al.
Published: (2025)

Data Sharing at the Edge of the Network: A Disturbance Resilient Multi-modal ITS
by: Mikolasek, Igor, et al.
Published: (2024)

Belief States for Cooperative Multi-Agent Reinforcement Learning under Partial Observability
by: Pritz, Paul J., et al.
Published: (2025)

AndroidWorld: A Dynamic Benchmarking Environment for Autonomous Agents
by: Rawles, Christopher, et al.
Published: (2024)

Observation Adaptation via Annealed Importance Resampling for Partially Observable Markov Decision Processes
by: Zhang, Yunuo, et al.
Published: (2025)

Adaptive Memory Crystallization for Autonomous AI Agent Learning in Dynamic Environments
by: Khanda, Rajat, et al.
Published: (2026)

Decision Transformer as a Foundation Model for Partially Observable Continuous Control
by: Zhang, Xiangyuan, et al.
Published: (2024)

Inferring Reward Machines and Transition Machines from Partially Observable Markov Decision Processes
by: Wu, Yuly, et al.
Published: (2025)

Near-Optimal Partially Observable Reinforcement Learning with Partial Online State Information
by: Shi, Ming, et al.
Published: (2023)

Decision Making in Non-Stationary Environments with Policy-Augmented Search
by: Pettet, Ava, et al.
Published: (2024)

Zero-Shot Reinforcement Learning Under Partial Observability
by: Jeen, Scott, et al.
Published: (2025)

Multi-View Causal Representation Learning with Partial Observability
by: Yao, Dingling, et al.
Published: (2023)

Guided Policy Optimization under Partial Observability
by: Li, Yueheng, et al.
Published: (2025)

A Sparsity Principle for Partially Observable Causal Representation Learning
by: Xu, Danru, et al.
Published: (2024)

Augmented Reinforcement Learning Framework For Enhancing Decision-Making In Machine Learning Models Using External Agents
by: Singh, Sandesh Kumar
Published: (2025)

LLMs for Text-Based Exploration and Navigation Under Partial Observability
by: Sandfuchs, Stephan, et al.
Published: (2026)

Provable Representation with Efficient Planning for Partial Observable Reinforcement Learning
by: Zhang, Hongming, et al.
Published: (2023)

Verifiability-First Agents: Provable Observability and Lightweight Audit Agents for Controlling Autonomous LLM Systems
by: Gupta, Abhivansh
Published: (2025)

Recurrent Deep Reinforcement Learning for Chemotherapy Control under Partial Observability
by: Kiram, Firas Mohamed Elamine, et al.
Published: (2026)

Adversarial Latent-State Training for Robust Policies in Partially Observable Domains
by: Ahuja, Angad Singh
Published: (2026)

Partially Observable Gaussian Process Network and Doubly Stochastic Variational Inference
by: Kiroriwal, Saksham, et al.
Published: (2025)

Why Linear Recurrent Memory Works in Partially Observable Reinforcement Learning
by: Zhao, Yike, et al.
Published: (2026)

Scalable Decision-Making in Stochastic Environments through Learned Temporal Abstraction
by: Luo, Baiting, et al.
Published: (2025)

Demystifying the Physics of Deep Reinforcement Learning-Based Autonomous Vehicle Decision-Making
by: Wan, Hanxi, et al.
Published: (2024)

On the Role of Information Structure in Reinforcement Learning for Partially-Observable Sequential Teams and Games
by: Altabaa, Awni, et al.
Published: (2024)

Benchmarking Partial Observability in Reinforcement Learning with a Suite of Memory-Improvable Domains
by: Tao, Ruo Yu, et al.
Published: (2025)

A Convolution and Attention Based Encoder for Reinforcement Learning under Partial Observability
by: Wang, Wuhao, et al.
Published: (2025)

Pessimism in the Face of Confounders: Provably Efficient Offline Reinforcement Learning in Partially Observable Markov Decision Processes
by: Lu, Miao, et al.
Published: (2022)

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

LLMs are Greedy Agents: Effects of RL Fine-tuning on Decision-Making Abilities
by: Schmied, Thomas, et al.
Published: (2025)

Norm-Governed Multi-Agent Decision-Making in Simulator-Coupled Environments:The Reinsurance Constrained Multi-Agent Simulation Process (R-CMASP)
by: Dong, Stella C.
Published: (2025)

Learning Interpretable Policies in Hindsight-Observable POMDPs through Partially Supervised Reinforcement Learning
by: Lanier, Michael, et al.
Published: (2024)

Uncertainty Representations in State-Space Layers for Deep Reinforcement Learning under Partial Observability
by: Luis, Carlos E., et al.
Published: (2024)

Short-Term-to-Long-Term Memory Transfer for Knowledge Graphs under Partial Observability
by: Kim, Taewoon, et al.
Published: (2026)