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Interactive Collaborative Information Systems
The increasing complexity of our world demands new perspectives on the role of technology in human decision making. We need new technology to cope with the increasingly complex and information-rich nature of our modern society. This is particularly true for critical environments such as crisis manag...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor Corporativo: | |
| Otros Autores: | , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Berlin, Heidelberg :
Springer Berlin Heidelberg : Imprint: Springer,
2010.
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| Edición: | 1st ed. 2010. |
| Colección: | Studies in Computational Intelligence,
281 |
| Temas: | |
| Acceso en línea: | Texto Completo |
Tabla de Contenidos:
- Reinforcement Learning
- Approximate Dynamic Programming and Reinforcement Learning
- Learning with Whom to Communicate Using Relational Reinforcement Learning
- Switching between Representations in Reinforcement Learning
- Collaborative Decision Making
- A Decision-Theoretic Approach to Collaboration: Principal Description Methods and Efficient Heuristic Approximations
- Efficient Methods for Near-Optimal Sequential Decision Making under Uncertainty
- Ant Colony Learning Algorithm for Optimal Control
- Map-Based Support for Effective Collaboration in Micro-mobile Virtual Teams
- Computer-Human Interaction Modeling
- Affective Dialogue Management Using Factored POMDPs
- Context-Aware Multimodal Human-Computer Interaction
- Design Issues for Pen-Centric Interactive Maps
- Interacting with Adaptive Systems
- Example-Based Human Pose Recovery under Predicted Partial Occlusions
- Architectures for Distributed Agent-Actor Communities
- Agility and Adaptive Autonomy in Networked Organizations
- Adaptive Hierarchical Multi-agent Organizations
- Method for Designing Networking Adaptive Interactive Hybrid Systems
- Case Studies and Applications
- A Call for Sensemaking Support Systems in Crisis Management
- A Distributed Approach to Gas Detection and Source Localization Using Heterogeneous Information
- Traffic Light Control by Multiagent Reinforcement Learning Systems
- Fusing Heterogeneous and Unreliable Data from Traffic Sensors
- Bayesian Networks for Expert Systems: Theory and Practical Applications.