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CVIU
2010
163views more  CVIU 2010»
10 years 4 months ago
Automated handwashing assistance for persons with dementia using video and a partially observable Markov decision process
This paper presents a real-time vision-based system to assist a person with dementia wash their hands. The system uses only video inputs, and assistance is given as either verbal ...
Jesse Hoey, Pascal Poupart, Axel von Bertoldi, Tam...
CONNECTION
2008
178views more  CONNECTION 2008»
10 years 4 months ago
Spoken language interaction with model uncertainty: an adaptive human-robot interaction system
Spoken language is one of the most intuitive forms of interaction between humans and agents. Unfortunately, agents that interact with people using natural language often experienc...
Finale Doshi, Nicholas Roy
GECCO
2008
Springer
179views Optimization» more  GECCO 2008»
10 years 5 months ago
Emergent architecture in self organized swarm systems for military applications
Many sectors of the military are interested in Self-Organized (SO) systems because of their flexibility, versatility and economics. The military is researching and employing auto...
Dustin J. Nowak, Gary B. Lamont, Gilbert L. Peters...
ATAL
2010
Springer
10 years 5 months ago
Risk-sensitive planning in partially observable environments
Partially Observable Markov Decision Process (POMDP) is a popular framework for planning under uncertainty in partially observable domains. Yet, the POMDP model is riskneutral in ...
Janusz Marecki, Pradeep Varakantham
AAAI
1994
10 years 5 months ago
Acting Optimally in Partially Observable Stochastic Domains
In this paper, we describe the partially observable Markov decision process pomdp approach to nding optimal or near-optimal control strategies for partially observable stochastic ...
Anthony R. Cassandra, Leslie Pack Kaelbling, Micha...
UAI
2000
10 years 5 months ago
PEGASUS: A policy search method for large MDPs and POMDPs
We propose a new approach to the problem of searching a space of policies for a Markov decision process (MDP) or a partially observable Markov decision process (POMDP), given a mo...
Andrew Y. Ng, Michael I. Jordan
UAI
2003
10 years 5 months ago
Optimal Limited Contingency Planning
For a given problem, the optimal Markov policy over a finite horizon is a conditional plan containing a potentially large number of branches. However, there are applications wher...
Nicolas Meuleau, David E. Smith
AIPS
2000
10 years 5 months ago
On-line Scheduling via Sampling
1 We consider the problem of scheduling an unknown sequence of tasks for a single server as the tasks arrive with the goal off maximizing the total weighted value of the tasks serv...
Hyeong Soo Chang, Robert Givan, Edwin K. P. Chong
IJCAI
2003
10 years 5 months ago
Taming Decentralized POMDPs: Towards Efficient Policy Computation for Multiagent Settings
The problem of deriving joint policies for a group of agents that maximize some joint reward function can be modeled as a decentralized partially observable Markov decision proces...
Ranjit Nair, Milind Tambe, Makoto Yokoo, David V. ...
IJCAI
2003
10 years 5 months ago
A Planning Algorithm for Predictive State Representations
We address the problem of optimally controlling stochastic environments that are partially observable. The standard method for tackling such problems is to define and solve a Part...
Masoumeh T. Izadi, Doina Precup
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