A digital twin (DT) leverages a virtual representation of the physical world, along with
communication (eg, 6G), computing (eg, edge computing), and artificial intelligence (AI) …

Policy learning enables agents to learn how to map states to actions, thus enabling adaptive
and flexible behavioral generation in complex environments. Policy learning methods are …

We explore the viability of casting foundation models as generic reward functions for
reinforcement learning. To this end, we propose a simple pipeline that interfaces an off-the …

Imitation learning suffers from causal confusion. This phenomenon occurs when learned
policies attend to features that do not causally influence the expert actions but are instead …

In many real-world settings, an agent must learn to act in environments where no reward
signal can be specified, but a set of expert demonstrations is available. Imitation learning (IL) …

A digital twin (DT) leverages a virtual representation of the physical world, along with
communication (eg, 6G), computing (eg, edge computing), and artificial intelligence (AI) …