7 papers
Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments
Deepak Kumar Panda, Adolfo Perrusquia, Weisi Guo
Autonomous unmanned aerial vehicles (UAVs) increasingly rely on reinforcement learning (RL) for navigation. However, global navigation satellite system (GNSS) spoofing attacks can…
A Signal Contract for Online Language Grounding and Discovery in Decision-Making
Dimitris Panagopoulos, Adolfo Perrusquia, Weisi Guo
Autonomous systems increasingly receive time-sensitive contextual updates from humans through natural language, yet embedding language understanding inside decision-makers couples…
Dialogue Telemetry: Turn-Level Instrumentation for Autonomous Information Gathering
Dimitris Panagopoulos, Adolfo Perrusquia, Weisi Guo
Autonomous systems conducting schema-grounded information-gathering dialogues face an instrumentation gap, lacking turn-level observables for monitoring acquisition efficiency and…
Guaranteeing and Explaining Stability across Heterogeneous Load Balancing using Calculus Network Dynamics
Mengbang Zou, Yun Tang, Adolfo PerrusquÃa +1
Load balancing between base stations (BSs) allows BS capacity to be efficiently utilised and avoid outages. Currently, data-driven mechanisms strive to balance inter-BS load and re…
Learning What Matters Now: A Dual-Critic Context-Aware RL Framework for Priority-Driven Information Gain
Dimitris Panagopoulos, Adolfo Perrusquia, Weisi Guo
Autonomous systems operating in high-stakes search-and-rescue (SAR) missions must continuously gather mission-critical information while flexibly adapting to shifting operational p…
Selective Exploration and Information Gathering in Search and Rescue Using Hierarchical Learning Guided by Natural Language Input
Dimitrios Panagopoulos, Adolfo Perrusquia, Weisi Guo
In recent years, robots and autonomous systems have become increasingly integral to our daily lives, offering solutions to complex problems across various domains. Their applicatio…