Learning Graphical Models
Agent Planning with World Knowledge Model
Imitating humans' mental world knowledge model which provides global prior knowledge before the task and maintains local dynamic knowledge during the task, in this paper, we introduce parametric W orld K nowledge M odel ( WKM) to facilitate agent
Model and Feature Diversity for Bayesian Neural Networks in Mutual Learning
Utilizing mutual learning can effectively enhance the performance of peer BNNs.
Meta-Learning Universal Priors Using Non-Injective Change of Variables
Critical in this context is the prior knowledge accumulated from related tasks.
Rehearsal Learning for Avoiding Undesired Future
Machine learning (ML) models have been widely used to make predictions.
N-Agent Ad Hoc Teamwork
Current approaches to learning cooperative multi-agent behaviors assume relatively restrictive settings.
Decision Stacks: Flexible Reinforcement Learning via Modular Generative Models
Modularity is a critical design principle for both software systems and artificial intelligence (AI).
Online POMDP Planning with Anytime Deterministic Guarantees
Autonomous agents operating in real-world scenarios frequently encounter uncertainty and make decisions based on incomplete information.