Driverless electric taxi fleets get smarter about uncertainty
A Chalmers University modelling study combined Bayesian forecasts with transparent optimisation to coordinate large self-driving electric taxi fleets under uncertain ...
A Chalmers University modelling study combined Bayesian forecasts with transparent optimisation to coordinate large self-driving electric taxi fleets under uncertain ...
A cloud-native agentic AI framework combining reinforcement learning, large-language-model artifact generation and policy-as-code controls achieved 91.4% mean resolution success across ...
A reinforcement-learning method combining contraction theory was tested in simulation and on three robot platforms, providing stability guarantees and improving ...
A systems-oriented review reports that AI is applied across solar, hydropower and wind systems, with deep learning prominent in forecasting ...
A multi-objective reinforcement-learning system reduced cobot trajectory error, collisions, cycle time, and energy use in a controlled simulation benchmark, while ...
A new cloud-edge framework transmits only a losslessly compressed ControlNet condition instead of the raw reference image, cutting uplink payloads ...
A new open-access cross-domain review maps how the same AI algorithms recur across IoT security, network routing, computer vision, and ...
A new MARL framework guided by MPC expert knowledge achieves coordinated frequency control across interconnected microgrids, with pass rates up ...
A new hybrid Pareto-safe distributional reinforcement learning scheduler balances latency, energy, SLA, and load balance in cloud task allocation while ...
A new review maps how advances in computer vision, vision language models and reinforcement learning could enable collaborative robots to ...
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© 2025 Scienmag - Science Magazine