Learning Weak Constraints in Answer Set Programming

This paper contributes to the area of inductive logic programming by presenting a new learning framework that allows the learning of weak constraints in Answer Set Programming (ASP). The framework, called Learning from Ordered Answer Sets, generalises our previous work on learning ASP programs without weak constraints, by considering a new notion of examples as ordered pairs of partial answer sets that exemplify which answer sets of a learned hypothesis (together with a given background knowledge) are preferred to others. In this new learning task inductive solutions are searched within a hypothesis space of normal rules, choice rules, and hard and weak constraints. We propose a new algorithm, ILASP2, which is sound and complete with respect to our new learning framework. We investigate its applicability to learning preferences in an interview scheduling problem and also demonstrate that when restricted to the task of learning ASP programs without weak constraints, ILASP2 can be much more efficient than our previously proposed system.Comment: To appear in Theory and Practice of Logic Programming (TPLP), Proceedings of ICLP 201

Virtual Alchemies: Can New Learning Technologies Transform Police Training?

This was a collaborative action research project with three, mixed method evaluation cycles. Its aim was to increase the impact of new learning technologies (NLT) in two Police Forces. The first reconnaissance cycle found a significant absence of uptake for one computer based training system (<1% impact after five years) with only assumptions of ‘technological determinism’ driving the process. A range of individual, work related and cultural factors were illuminated, towards understanding how the Force might become a ‘network’ organisation, where technology fundamentally transforms how work is done (Symon, 2000). Following the qualitative interview study, a quantitative survey was carried out with 164 respondents on the areas of concern for NLT in the Police. Factor analysis of this data reinforced a parsimonious five factor solution, accounting for 55% of the variance and on which to proceed with cycles two and three. In the second cycle, 130 Police Probationers completed a battery of psychometrics to assess individual difference factors associated with successful outcomes in training with NLT. Results showed 27% of the variance on a bespoke NLT learning measure was predicted by computer attitudes. Age, gender, education, motivational and almost all personality measures offered no significant contribution to explaining the data. The bespoke learning criterion was used as a pre-test, post-test and retention measure and showed significant increases in knowledge were gained from NLT: effective and efficient learning was evidenced. Also in the second cycle, a sub-sample of (n=20-34) Probationers participated in two stages of repertory grid interviews rating different elements of Police training methods. From these data an ‘Ideal Probationer Learning Event’ (IPLE) model was proposed. This was stable over time and positioned NLT within a conceptual structure that identified preferred and non-preferred construct poles equating to four dimensions along which Police officers reliably rated any training event. In essence, it highlighted sites of perceived credibility and offered these as levers for creative change. Follow-up work with 120 Probationers using another example of NLT explored how integration of learning from NLT could occur from a learner-centered point of view, using an interpretive concept mapping technique. This illuminated sites of power exchange and the location of ‘ownership’ of learning in Police culture. The IPLE model was used to direct the third cycle which included constructivist and contingency perspectives. It was propsed that by creatively designing an NLT event to increase elements of the preferred constructs discovered in cycle two, integration of an NLT event would enable the transformative properties of NLT as a to manifest themselves. A sample of up to 60 Police Staff used an NLT package alongside a bespoke, collaborative e-learning group. Criterions were developed according to skill breadth, frequency and difficulty and significant increases in learning were not only found, but maintained following completion of NLT when retention was measured. The e-learning group brought some of the credible elements of training to the NLT event, thereby constituting a ‘unique solution’ (Seltzer, 1971). It created peer learning groups, despite geographical separation. Data for each level of Kirkpatrick’s (1959; 1960) ‘best practice’ training evaluation model was collected enabling the conclusion that creative integration is key to a network uptake of NLT