Help me to help you: How to learn intentions, actions and plans

The collaboration between a human and a robot is here understood as a learning process mediated by the instructor prompt behaviours and the apprentice collecting information from them to learn a plan. The instructor wears the Gaze Machine, a wearable device gathering and conveying visual and audio input from the instructor while executing a task. The robot, on the other hand, is eager to learn both the best sequence of actions, their timing and how they interlace. The cross relation among actions is specified both in terms of time intervals for their execution, and in terms of location in space to cope with the instruction interaction with people and objects in the scene. We outline this process: how to transform the rich information delivered by the Gaze Machine into a plan. Specifically, how to obtain a map of the instructor positions and his gaze position, via visual slam and gaze fixations; further, how to obtain an action map from the running commentaries and the topological maps and, finally, how to obtain a temporal net of the relevant actions that have been extracted. The learned structure is then managed by the flexible time paradigm of flexible planning in the Situation Calculus for execution monitoring and plan generation. Copyright © 2011, Association for the Advancement of Artificial Intelligence. All rights reserved

A unified framework for planning and execution-monitoring of mobile robots

We present an original integration of high level planning and execution with incoming perceptual information from vision, SLAM, topological map segmentation and dialogue. The task of the robot system, implementing the integrated model, is to explore unknown areas and report detected objects to an operator, by speaking loudly. The knowledge base of the planner maintains a graph-based representation of the metric map that is dynamically constructed via an unsupervised topological segmentation method, and augmented with information about the type and position of detected objects, within the map, such as cars or containers. According to this knowledge the cognitive robot can infer strategies in so generating parametric plans that are instantiated from the perceptual processes. Finally, a model-based approach for the execution and control of the robot system is proposed to monitor, concurrently, the low level status of the system and the execution of the activities, in order to achieve the goal, instructed by the operator. Copyright © 2011, Association for the Advancement of Artificial Intelligence. All rights reserved

Comparing clinician and patient perspectives in the management of hot flushes in UK breast cancer patients

Introduction Women who have been treated for breast cancer identify vasomotor symptoms, such as hot flushes and night sweats (HFNS), as a serious problem. An estimated 550 000 people live in the UK today with a diagnosis of breast cancer and up to 70% experience HFNS. Estrogen replacement remains the most effective treatment for hot flushes. However, this is contraindicated in the majority of women with estrogen‐dependent breast cancer. Fewer than 50% of women with estrogen receptor (ER) ‐positive breast cancer complete the recommended 5 years of endocrine treatment—tamoxifen and aromatase inhibitors (AIs). This lack of adherence leads to a 20% excess breast cancer mortality. This lack of adherence may be due to unacceptable side effects such as HFNS. Objectives Patient members of the National Cancer Research Institute UK Breast Clinical Studies Group identified that there is very little research into the management of symptoms after breast cancer treatment. In response we established a Working Party on Symptom Management. The members all have a particular interest in the management of HFNS, and include patients, as well as clinical and academic partners representing oncology, psychology, gynaecology, complementary therapies and the voluntary sector. Methods We gauged current clinical practice of the management of HFNS by surveying breast cancer patients, general practitioners (GPs) and healthcare professionals (HCPs) and we will present these data. Results Forty percent of patients reported that no HCPs or GPs had asked them about HFNS. Despite >90% of GPs and HCPs reporting that they prescribed drugs to alleviate HFNS, only 26% of the patients had been offered drugs and fewer than 2% said they helped; 31% of the patients said that the HFNS were severe enough for them to consider stopping endocrine therapy. Conclusion If women are to be helped to adhere to their life‐saving treatment, new approaches need to be developed to ameliorate HFNS