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Found 6 papers, 2 papers with code
Monte Carlo Tree Search with Boltzmann Exploration
Monte-Carlo Tree Search (MCTS) methods, such as Upper Confidence Bound applied to Trees (UCT), are instrumental to automated planning techniques.
Beta Residuals: Improving Fault-Tolerant Control for Sensory Faults via Bayesian Inference and Precision Learning
Model-based fault-tolerant control (FTC) often consists of two distinct steps: fault detection & isolation (FDI), and fault accommodation.
Active Inference in Robotics and Artificial Agents: Survey and Challenges
Active inference is a mathematical framework which originated in computational neuroscience as a theory of how the brain implements action, perception and learning.
On Solving a Stochastic Shortest-Path Markov Decision Process as Probabilistic Inference
Previous work on planning as active inference addresses finite horizon problems and solutions valid for online planning.
Towards Stochastic Fault-tolerant Control using Precision Learning and Active Inference
This work presents a fault-tolerant control scheme for sensory faults in robotic manipulators based on active inference.
Active Inference for Integrated State-Estimation, Control, and Learning
This work presents an approach for control, state-estimation and learning model (hyper)parameters for robotic manipulators.
Robotics
