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Evidence-Gated Matched-Pulse Transport is proposed, an intervention-based Bayesian procedure that couples fault localization with estimation of actuator effectiveness through a shared matched-response representation, thereby preserving diagnostic reliability while converting localized evidence into recovery-relevant un...
CREW (Collaborative Reinforcement Learning for Related Work Generation) is proposed, a novel framework where LLM agents bypass heuristic pipelines to dynamically coordinate by autonomously selecting actions, driven by a policy optimized via Independent Proximal Policy Optimization (IPPO).
The Coordinated Truck-Drone Routing with Time Windows and Backhauls poses a complex challenge in collaborative logistics, requiring tight coordination between ground vehicles and drones under stringent operational constraints. Unlike traditional back-haul routing models that impose a strict priority between linehaul de...
SCOPE reframes objective design as a mechanism for guiding policy exploration, enabling the search process to exploit observed evidence while maintaining structured diversity across discrete solution spaces and generalizes well across diverse combinatorial structures.
A novel genetic programming algorithm is proposed that is Hybrid Crossover Genetic Programming featuring two distinct crossover operators to tackle the dynamic vehicle routing problem with drone and time window constraints and is highly effective, achieving fast convergence and consistently outperforming the existing m...
Multi-agent planning becomes substantially harder when agents must improve specialized decision-making skills while keeping their executable implementations private. This setting arises when independently developed agents expose heterogeneous interfaces, observations, and capabilities, yet must coordinate under a share...
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