Info
- Utilizzare la checkbox di selezione a fianco di ciascun documento per attivare le funzionalità di stampa, invio email, download nei formati disponibili del (i) record.
Artificial Superintelligence: Coordination & Strategy
| Artificial Superintelligence: Coordination & Strategy |
| Autore | Yampolskiy Roman |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
| Descrizione fisica | 1 electronic resource (206 p.) |
| Soggetto non controllato |
strategic oversight
multi-agent systems autonomous distributed system artificial superintelligence safe for design adaptive learning systems explainable AI ethics scenario mapping typologies of AI policy artificial intelligence design for values distributed goals management scenario analysis Goodhart’s Law specification gaming AI Thinking VSD AI human-in-the-loop value sensitive design future-ready forecasting AI behavior AI arms race AI alignment blockchain artilects policy making on AI distributed ledger AI risk Bayesian networks artificial intelligence safety conflict AI welfare science moral and ethical behavior scenario network mapping policymaking process human-centric reasoning antispeciesism AI forecasting transformative AI ASILOMAR judgmental distillation mapping terraforming pedagogical motif AI welfare policies superintelligence artificial general intelligence supermorality AI value alignment AGI predictive optimization AI safety technological singularity machine learning holistic forecasting framework simulations existential risk technology forecasting AI governance sentiocentrism AI containment |
| ISBN | 3-03921-854-9 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | Artificial Superintelligence |
| Record Nr. | UNINA-9910404084203321 |
Yampolskiy Roman
|
||
| MDPI - Multidisciplinary Digital Publishing Institute, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Combining Sensors and Multibody Models for Applications in Vehicles, Machines, Robots and Humans
| Combining Sensors and Multibody Models for Applications in Vehicles, Machines, Robots and Humans |
| Autore | Cuadrado Javier |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 electronic resource (256 p.) |
| Soggetto topico | Technology: general issues |
| Soggetto non controllato |
Kalman filter
motion capture gait analysis inertial sensor rail vehicles track irregularities multibody dynamics inertial sensors computer vision singular configuration parallel robot motion control 3D tracking screw theory Kalman filtering coupled states-inputs estimation virtual sensors slider-crank mechanism virtual sensoring physical sensors smart/intelligent sensors sensor technology and applications sensing principles signal processing in sensor systems symbolic generation real-time computation human-in-the-loop haptic devices parameter estimation curve fitting method hydraulic system predictive maintenance characteristic curve product life cycle digital twin adaptive Kalman filter nonlinear models virtual sensing multibody based observers vehicle dynamics estimation sideslip angle estimation factor graph graphical models movable repetitive lander fault-tolerant soft-landing landing configuration stability optimization |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557337203321 |
|
Cuadrado Javier
|
||
| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||