Interactive Collaborative Information SystemsRobert Babuška, Frans C.A. Groen The increasing complexity of our world demands new perspectives on the role of technology in decision making. Human decision making has its li- tations in terms of information-processing capacity. 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 management and tra?c management, where humans need to engage in close collaborations with arti?cial systems to observe and understand the situation and respond in a sensible way. We believe that close collaborations between humans and arti?cial systems will become essential and that the importance of research into Interactive Collaborative Information Systems (ICIS) is self-evident. Developments in information and communication technology have ra- cally changed our working environments. The vast amount of information available nowadays and the wirelessly networked nature of our modern so- ety open up new opportunities to handle di?cult decision-making situations such as computer-supported situation assessment and distributed decision making. To make good use of these new possibilities, we need to update our traditional views on the role and capabilities of information systems. The aim of the Interactive Collaborative Information Systems project is to develop techniques that support humans in complex information en- ronments and that facilitate distributed decision-making capabilities. ICIS emphasizes the importance of building actor-agent communities: close c- laborations between human and arti?cial actors that highlight their comp- mentary capabilities, and in which task distribution is ?exible and adaptive. |
Other editions - View all
Interactive Collaborative Information Systems Robert Babu Ka,Frans C. A. Groen No preview available - 2010 |
Interactive Collaborative Information Systems Robert Babuška,Frans C.A. Groen No preview available - 2012 |
Common terms and phrases
action adaptive agent algorithm application approach approximate Artificial Intelligence autonomy Bayesian networks behavior belief Bellman equation chapter Collaborative communication complex Computer Computer Vision Conference context convergence coordination crisis management Dec-POMDP defined described distribution domain dynamic dynamic programming environment estimation EUPM evaluation example factor filter framework fusion fuzzy gestures goal hierarchy human I-POMDP icons IEEE input interaction interface joint Machine Learning Markov decision processes Markov property method multi-agent multi-agent systems multimodal Netherlands Netherlands e-mail nodes observation model optimal optimal control organization organizational parameters partially observable performance pheromone policy iteration POMDP pose probability problem Q-function Q-iteration Q-learning recognition reinforcement learning relations representation rescue reward role samples scenario selected Sensemaking sensors simulation situation solution space specific speed Springer structure task teams techniques Technology tion transition trust update user’s value function value iteration variables vector vehicle