reinforcement learning

LGBTIQ+ lives under colonial shadows: The legacy of German colonial law in today’s Tanzania and Namibia

Colonial legacies have profoundly shaped the post-colonial landscapes of African countries, influencing all aspects of life, including the reinforcement of a singular, heteronormative conception of sexuality. This legacy continues to shape the perceptions of sexual orientation, gender identity, gender expression and se...

A cascaded PID-reinforcement learning-based virtual inertia control in microgrid load frequency control system using electric vehicle energy storage

The islanded microgrids increasingly depend on renewable energy sources for power generation and introduce significant frequency control challenges due to the renewable sources’ intermittent nature and low system inertia. Traditional energy storage systems, though employed and effective for frequency stabilization, are...

Artificial Intelligence for Economic Resilience and Global Stability

The current world economies are in a highly volatile framework characterized by thick interdependencies, and quick changing risk factors. The classical econometric models with their assumption of the stasis and restrictive data granularity cannot predict systemic shocks and timely interventions. This chapter provides a...

Energy-cost-aware cooperative scheduling for cascade slurry pumping stations: A multi-agent deep reinforcement learning approach

Robust indoor automated guided vehicle navigation for logistics applications via imitation-augmented hierarchical reinforcement learning with a memory-attention generalized network

Comportamientos exitosos del trabajo en suelo durante el campeonato venezolano de Judo 2025, primera categoría: Estudio Observacional

The aim of this investigation was to determine sucessfull behaviors asociated to grounwork from the participants. Under a non-experimental design, 51 actions from 1477 performed attacks were evaluated by: Submission form (inmobilization, strangled, articular luxation); precedent maneuvers, opponent initial position, pe...

Cooperative control of multi-microgrids under uncertainty: a multi-agent actor-critic approach with LSTM and deep dense architecture

The high penetration of renewable energy poses significant source-load uncertainty challenges to the economic and stable operation of microgrids. To address the key challenges of multi-microgrid cooperative optimization, including temporal source-load uncertainty, heterogeneous inter-microgrid coordination, and real-ti...

Optimization of dynamic admission control for preemptible cloud services based on TPD-SAC reinforcement learning

Abstract Preemptible cloud services utilize idle resources from contract-based services. The resources allocated to these low-priority services can be preempted by contract-based services during periods of overload, so cloud platforms offer low prices to attract cost-sensitive users. While preemptible cloud services en...

Social information quality and environmental volatility shape collective foraging behaviour

Abstract Collective foraging is widespread across the animal kingdom, allowing animals to more effectively discover resources. However, collective foragers need to balance a key trade-off between private exploration and using social information. Social information can come in very distinct forms, ranging from simple po...

AI-Driven Autonomous Test Automation Frameworks for Cloud Native Applications: Improving Software Reliability and Continuous Delivery

This paper describes a framework that brings together three capabilities: automatic generation of new test cases from API specifications and usage data, self-healing of broken test scripts through similarity-based and learned matching, and risk-based prioritisation of test execution using a reinforcement learning agent...

AI-Based Optimization for Biofuel Production: Strategies for Utilizing Degraded Land for Climate Change Mitigation, Green Finance Mobilization, and Achieving United Nations Sustainable Development Goals

Global land degradation affects approximately 2 billion hectares, threatening food security, biodiversity, and climate stability while undermining the United Nations Sustainable Development Goals (SDGs). The concurrent urgency to decarbonize the energy system and mobilize green finance for sustainable transitions has c...

Learning from Unreachable Rewards: Hint-Conditioned Reinforcement Learning for Generative Recommendation

This work proposes Hint-Conditioned Generative Recommendation (HCGRec), a semantic-ID generative recommendation framework that recovers learning signal for such hard training instances and introduces hint-aware credit decomposition, using supervised learning to preserve item-semantic and prefix-structure alignment for...