Artificial intelligence is revolutionising quantitative finance, enabling smarter trading through advanced models, feature ...

AI is a set of algorithms capable of solving problems. But how relevant are they to the tasks that EDA performs?

The Parallel-R1 framework uses reinforcement learning to teach models how to explore multiple reasoning paths at once, ...

KAIST research team's independently developed humanoid robot boasts world-class driving performance, reaching speeds of 12km/h, along with excellent stability, maintaining balance even with its eyes ...

Heal,” designed by engineers at UC Santa Cruz, aims to optimize each stage of wound healing the process. Preclinical tests ...

A (NRL) research team successfully conducted the first reinforcement learning (RL) control of a free-flyer in space on May 27 ...

Picture this: a self-driving car smoothly navigating treacherous mountain roads with consecutive hairpin turns – a scenario ...

David Silver of Google DeepMind thinks AIs that ‘learn by experience’ are the future of AI – but maybe not in particle ...

Pairing artificial intelligence techniques called Q-learning and advantage actor-critic provides new way to optimize hybrid photovoltaic-thermoelectric systems.

Objective: To develop a self-reportable risk assessment tool for elderly type 2 diabetes mellitus (T2DM) patients, evaluating risks of diabetic nephropathy (DN), retinopathy (DR), peripheral ...

Abstract: Multiobjective reinforcement learning (MORL) aims to seek a complete Pareto front (PF) with different compromise policies in multiobjective Markov decision processes (MOMDPs). However, most ...

Abstract: This study introduces a novel finite time fault tolerant controller integrating nonsingular terminal sliding mode (NTSM) and reinforcement learning (RL) strategies for manipulator systems ...