A new approach to plan-space explanation: analyzing plan-property dependencies in oversubscription planning

In many usage scenarios of AI Planning technology, users will want not just a plan π but an explanation of the space of possible plans, justifying π. In particular, in oversubscription planning where not all goals can be achieved, users may ask why a conjunction A of goals is not achieved by π. We propose to answer this kind of question with the goal conjunctions B excluded by A, i. e., that could not be achieved if A were to be enforced. We formalize this approach in terms of plan-property dependencies, where plan properties are propositional formulas over the goals achieved by a plan, and dependencies are entailment relations in plan space. We focus on entailment relations of the form ∧g∈A g ⇒ ⌝ ∧g∈B g, and devise analysis techniques globally identifying all such relations, or locally identifying the implications of a single given plan property (user question) ∧g∈A g. We show how, via compilation, one can analyze dependencies between a richer form of plan properties, specifying formulas over action subsets touched by the plan. We run comprehensive experiments on adapted IPC benchmarks, and find that the suggested analyses are reasonably feasible at the global level, and become significantly more effective at the local level

Predictors of positive treatment outcome in people with anorexia nervosa treated in a specialized inpatient unit: The role of early response to treatment

o investigate factors which predict positive treatment outcome in inpatients with anorexia nervosa (AN), particularly the role of early treatment response. METHOD: 102 patients entering specialist inpatient treatment were assessed for eating disorder history, psychopathology and motivation to change. Predictive factors assessed were: early treatment response defined as weight increase of at least 0.5-1 kg/week during the first six weeks of treatment; admission BMI; onset age; chronicity; motivation to change; diagnosis; and previous hospitalization for AN. Positive treatment outcome was defined as achieving BMI 17.5 kg/m2 within an individual timeframe. RESULTS: Logistic regression indicated that patients were 18 times more likely to reach positive treatment outcome if they met NICE weight guidelines within the first six weeks of hospitalization. Higher admission BMI was also found to predict positive treatment outcome. DISCUSSION: Higher entry BMI and early weight gain predict positive treatment outcome in individuals receiving specialist AN inpatient treatment

Evaluation of a motivation and psycho-educational guided self help intervention for people with eating disorders (MOPED)

High dropout rates and poor levels of engagement are well documented for patients with eating disorders. Utilising motivational techniques and providing psycho-education have been suggested as ways to reduce treatment disengagement. This study aimed to evaluate the effect of a newly developed motivational and psycho-educational guided self-help intervention (MOPED) for people with eating disorders on engagement and retention in therapy. Patients who received MOPED pre-treatment (n = 79) were compared to a diagnosis matched group of patients receiving treatment as usual (TAU; n = 79). The study found that patients receiving MOPED had a higher engagement rate than those within the TAU group. Specifically, patients in the anorexic spectrum were found to present with both higher rates of engagement and completion of therapy when issued with MOPED in comparison to TAU. Self-help packages using motivational style could be a valuable and cost effective intervention for patients with eating disorders

The clinical effectiveness and cost-effectiveness of a ‘stepping into day treatment’ approach versus inpatient treatment as usual for anorexia nervosa in adult specialist eating disorder services (DAISIES trial): a study protocol of a randomised controlled multi-centre open-label parallel group non-inferiority trial

BACKGROUND: Anorexia nervosa (AN) is a serious and disabling mental disorder with a high disease burden. In a proportion of cases, intensive hospital-based treatments, i.e. inpatient or day patient treatment, are required, with day patient treatment often being used as a 'step-down' treatment after a period of inpatient treatment. Demand for such treatment approaches has seen a sharp rise. Despite this, the relative merits of these approaches for patients, their families, and the NHS and wider society are relatively unknown. This paper describes the rationale for, and protocol of, a two-arm multi-centre open-label parallel group non-inferiority randomised controlled trial, evaluating the effectiveness and cost-effectiveness of these two intensive treatments for adults with severe AN: inpatient treatment as usual and a stepped care day patient approach (the combination of day patient treatment with the option of initial inpatient treatment for medical stabilisation). The main aim of this trial is to establish whether, in adults with severe AN, a stepped care day patient approach is non-inferior to inpatient treatment as usual in relation to improving body mass index (BMI) at 12 months post-randomisation. METHODS: 386 patients with a Diagnostic and Statistical Manual 5th edition diagnosis of severe AN or related disorder, with a BMI of ≤16 kg/m2 and in need of intensive treatment will be randomly allocated to either inpatient treatment as usual or a stepped care day patient approach. Patients in both groups will receive treatment until they reach a healthy weight or get as close to this point as possible. Assessments will be conducted at baseline (prior to randomisation), and at 6 and 12 months post-randomisation, with additional monthly symptom monitoring. The primary outcome will be BMI at the 12-month post-randomisation assessment. Other outcomes will include psychosocial adjustment; treatment motivation, expectations and experiences; cost-effectiveness; and carer burden. DISCUSSION: The results of this study will provide a rigorous evaluation of two intensive treatment approaches which will inform future national and international treatment guidelines and service provision

Evidencing the impact of teaching-related CPD: beyond the ‘Happy Sheets’

peerreview_statement: The publishing and review policy for this title is described in its Aims & Scope. aims_and_scope_url: http://www.tandfonline.com/action/journalInformation?show=aimsScope&journalCode=rija2

Explaining the space of plans through plan-property dependencies

A key problem in explainable AI planning is to elucidate decision rationales. User questions in this context are often contrastive, taking the form “Why do A rather than B?”. Answering such a question requires a statement about the space of possible plans. We propose to do so through plan-property dependencies, where plan properties are Boolean properties of plans the user is interested in, and dependencies are entailment relations in plan space. The answer to the above question then consists of those properties C entailed by B. We introduce a formal framework for such dependency analysis. We instantiate and operationalize that framework for the case of dependencies between goals in oversubscription planning. More powerful plan properties can be compiled into that special case. We show experimentally that, in a variety of benchmarks, the suggested analyses can be feasible and produce compact answers for human inspection

Blueprint for a Simulation Framework to Increase Driver Training Safety in North America: Case Study

Despite numerous recent advances in the classroom and in-vehicle driver training and education over the last quarter-century, traffic accidents remain a leading cause of mortality for young adults—particularly, those between the ages of 16 and 19. Obviously, despite recent advances in conventional driver training (e.g., classroom, in-vehicle, Graduated Driver Licensing programs), this remains a critical public safety and public health concern. As advanced vehicle technologies continue to evolve, so too does the unintended potential for mechanical, visual, and/or cognitive driver distraction and adverse safety events on national highways. For these reasons, a physics-based modeling and high-fidelity simulation have great potential to serve as a critical supplementary component of a near-future teen-driver training framework. Here, a case study is presented that examines the specification, development, and deployment of a “blueprint” for a simulation framework intended to increase driver training safety in North America. A multi-measure assessment of simulated driver performance was developed and instituted, including quantitative (e.g., simulator-measured), qualitative (e.g., evaluator-observed), and self-report metrics. Preliminary findings are presented, along with a summary of novel contributions through the deployment of the training framework, as well as planned improvements and suggestions for future directions