AbstractThis paper describes a process by which anthropologists, computer scientists, and social welfare case managers collaborated to build a stochastic model of welfare advising in Kentucky. In the process of collaboration, the research team rethought the Bayesian network model of Markov decision processes and designed a new knowledge elicitation format. We expect that this model will have wide applicability in other domains
Large investments are made annually to develop and maintain IT systems. Successful outcome of IT pro...
People combine their abstract knowledge about the world with data they have gathered in order to gui...
Bayesian decision theory provides a strong theoretical basis for a single-participant decision makin...
This paper describes a process by which anthropologists, computer scientists, and social welfare cas...
AbstractThis paper describes a process by which anthropologists, computer scientists, and social wel...
We introduce a new variant of Markov decision processes called MDPs with action results, and a varia...
Information analysis and decision making are complex processes given that the sources of information...
We live in an era where every human entity, from a simple citizen to the head of an entity as large ...
In this article, we apply the ideas of collaborative filtering to the problem of building dynamic Ba...
The last five years have seen a surge in interest in the use of techniques from Bayesian decision th...
Relationship between agents in a society can be rep-resented as a network structure where the nodes ...
AbstractModelling cultural ecosystem services is challenging as they often involve subjective and in...
Bayesian networks are a popular mechanism for dealing with uncertainty in complex situations. They a...
The planet we are living on is getting small; each decade the number of people here grows by almost ...
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Com...
Large investments are made annually to develop and maintain IT systems. Successful outcome of IT pro...
People combine their abstract knowledge about the world with data they have gathered in order to gui...
Bayesian decision theory provides a strong theoretical basis for a single-participant decision makin...
This paper describes a process by which anthropologists, computer scientists, and social welfare cas...
AbstractThis paper describes a process by which anthropologists, computer scientists, and social wel...
We introduce a new variant of Markov decision processes called MDPs with action results, and a varia...
Information analysis and decision making are complex processes given that the sources of information...
We live in an era where every human entity, from a simple citizen to the head of an entity as large ...
In this article, we apply the ideas of collaborative filtering to the problem of building dynamic Ba...
The last five years have seen a surge in interest in the use of techniques from Bayesian decision th...
Relationship between agents in a society can be rep-resented as a network structure where the nodes ...
AbstractModelling cultural ecosystem services is challenging as they often involve subjective and in...
Bayesian networks are a popular mechanism for dealing with uncertainty in complex situations. They a...
The planet we are living on is getting small; each decade the number of people here grows by almost ...
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Com...
Large investments are made annually to develop and maintain IT systems. Successful outcome of IT pro...
People combine their abstract knowledge about the world with data they have gathered in order to gui...
Bayesian decision theory provides a strong theoretical basis for a single-participant decision makin...