Testing a system specified using Statecharts and Z

A hybrid specification language SZ, in which the dynamic behaviour of a system is described using Statecharts and the data and the data transformations are described using Z, has been developed for the specification of embedded systems. This paper describes an approach to testing from a deterministic sequential specification written in SZ. By considering the Z specifications of the operations, the extended finite state machine (EFSM) defined by the Statechart can be rewritten to produce an EFSM that has a number of properties that simplify test generation. Test generation algorithms are introduced and applied to an example. While this paper considers SZ specifications, the approaches described might be applied whenever the specification is an EFSM whose states and transitions are specified using a language similar to Z

Biomorpher: interactive evolution for parametric design

Combining graph-based parametric design with metaheuristic solvers has to date focussed solely on performance based criteria and solving clearly defined objectives. In this paper, we outline a new method for combining a parametric modelling environment with an interactive Cluster-Orientated Genetic Algorithm (COGA). In addition to performance criteria, evolutionary design exploration can be guided through choice alone, with user motivation that cannot be easily defined. As well as numeric parameters forming a genotype, the evolution of whole parametric definitions is discussed through the use of genetic programming. Visualisation techniques that enable mixing small populations for interactive evolution with large populations for performance-based optimisation are discussed, with examples from both academia and industry showing a wide range of applications

Confidence in uncertainty: Error cost and commitment in early speech hypotheses

© 2018 Loth et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Interactions with artificial agents often lack immediacy because agents respond slower than their users expect. Automatic speech recognisers introduce this delay by analysing a user’s utterance only after it has been completed. Early, uncertain hypotheses of incremental speech recognisers can enable artificial agents to respond more timely. However, these hypotheses may change significantly with each update. Therefore, an already initiated action may turn into an error and invoke error cost. We investigated whether humans would use uncertain hypotheses for planning ahead and/or initiating their response. We designed a Ghost-in-the-Machine study in a bar scenario. A human participant controlled a bartending robot and perceived the scene only through its recognisers. The results showed that participants used uncertain hypotheses for selecting the best matching action. This is comparable to computing the utility of dialogue moves. Participants evaluated the available evidence and the error cost of their actions prior to initiating them. If the error cost was low, the participants initiated their response with only suggestive evidence. Otherwise, they waited for additional, more confident hypotheses if they still had time to do so. If there was time pressure but only little evidence, participants grounded their understanding with echo questions. These findings contribute to a psychologically plausible policy for human-robot interaction that enables artificial agents to respond more timely and socially appropriately under uncertainty

Pharmacokinetic profile of single and repeated oral doses of MDMA in squirrel monkeys: Relationship to lasting effects on brain serotonin neurons

A large body of data indicates that (7)3,4-methylenedioxymethamphetamine (MDMA, ‘ecstasy’) can damage brain serotonin neurons in animals. However, the relevance of these preclinical data to humans is uncertain, because doses and routes of administration used in animals have generally differed from those used by humans. Here, we examined the pharmacokinetic profile of MDMA in squirrel monkeys after different routes of administration, and explored the relationship between acute plasma MDMA concentrations after repeated oral dosing and subsequent brain serotonin deficits. Oral MDMA administration engendered a plasma profile of MDMA in squirrel monkeys resembling that seen in humans, although the half-life of MDMA in monkeys is shorter (3 vs 6–9 h). MDMA was biotransformed into MDA, and the plasma ratio of MDA to MDMA was 3–5/100, similar to that in humans. MDMA accumulation in squirrel monkeys was nonlinear, and plasma levels were highly correlated with regional brain serotonin deficits observed 2 weeks later. The present results indicate that plasma concentrations of MDMA shown here to produce lasting serotonergic deficits in squirrel monkeys overlap those reported by other laboratories in some recreational ‘ecstasy’ consumers, and are two to three times higher than those found in humans administered a single 100–150 mg dose of MDMA in a controlled setting. Additional studies are needed on the relative sensitivity of brain serotonin neurons to MDMA toxicity in humans and non-human primates, the pharmacokinetic parameter(s) of MDMA most closely linked to the neurotoxic process, and metabolites other than MDA that may play a role.Annis Mechan, Jie Yuan, George Hatzidimitriou, Rodney J Irvine, Una D McCann and George A Ricaurt