Prostate cancer is the most common solid tumor in American men and is screened for using prostate-specific antigen (PSA) tests. We report on a non-stationary partially observable Markov decision process (POMDP) for prostate biopsy referral decisions. The core states are the patients’ prostate cancer related health states, and PSA test results are the observations. Transition probabilities and r...

This is a demonstration of a voice dialer, implemented as a partially observable Markov decision process (POMDP). A realtime graphical display shows the POMDP’s probability distribution over different possible dialog states, and shows how system output is generated and selected. The system demonstrated here includes several recent advances, including an action selection mechanism which unifies ...

conclusions based on the clinical and radiographic examinations, implant-tooth approximation (less than 1 mm or direct contact) is not related to pulp vitality of the tooth. further studies with larger sample sizes are necessary to confirm the results of the study. results among the 31 assessed implants and the adjacent intact teeth, 13 implants had direct contact and 18 implants had proximity ...

From 12.06.05 to 17.06.2005 the Dagstuhl Seminar 05241 Synthesis and Planning was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas ...

Goal Driven Autonomy (GDA) is an agent model for reasoning about goals while acting in a dynamic environment. Since anomalous events may cause an agent’s current goal to become invalid, GDA agents monitor the environment for such anomalies. When domains are both partially observable and dynamic, agents must reason about sensing and planning actions. Previous GDA work evaluated agents in domains...

We present a foveated gesture recognition system that guides an active camera to foveate salient features based on a reinforcement learning paradigm. Using vision routines previously implemented for an interactive environment, we determine the spatial location of salient body parts of a user and guide an active camera to obtain images of gestures or expressions. A hiddenstate reinforcement lear...

There are many sensing challenges for which one must balance the effectiveness of a given measurement with the associated sensing cost. For example, when performing a diagnosis a doctor must balance the cost and benefit of a given test (measurement), and the decision to stop sensing (stop performing tests) must account for the risk to the patient and doctor (malpractice) for a given diagnosis b...

We propose a novel approach, called parallel rollout, to solving (partially observable) Markov decision processes. Our approach generalizes the rollout algorithm of Bertsekas and Castanon (1999) by rolling out a set of multiple heuristic policies rather than a single policy. In particular, the parallel rollout approach aims at the class of problems where we have multiple heuristic policies avai...

We consider Incentive Decision Processes, where a principal seeks to reduce its costs due to another agent’s behavior, by offering incentives to the agent for alternate behavior. We focus on the case where a principal interacts with a greedy agent whose preferences are hidden and static. Though IDPs can be directly modeled as partially observable Markov decision processes (POMDP), we show that ...

V advisors often increase sales for those customers who find such online advice to be convenient and helpful. However, other customers take a more active role in their purchase decisions and prefer more detailed data. In general, we expect that websites are more preferred and increase sales if their characteristics (e.g., more detailed data) match customers’ cognitive styles (e.g., more analyti...