Values and actions in aversion

Model-based and model-free controllers can, in principle, learn arbitrary actions to optimize their behavior, at least those actions that can be expressed and explored. Indeed, these are often referred to as instrumental controllers because their choices are learned to be instrumental for the delivery of desired outcomes. Although this flexibility is very powerful, it comes with an attendant cost of learning. Evolution appears to have endowed everything from the simplest organisms to us with powerful, pre-specified, but inflexible alternatives. These responses are termed Pavlovian, after the famous Russian physiologist and psychologist Pavlov. The responses of the Pavlovian controller are determined by evolutionary (phylogenetic) considerations rather than (ontogenetic) aspects of the contingent development or learning of an individual. These responses directly interact with instrumental choices arising from goal-directed and habitual controllers. This interaction has been studied in a wealth of animal paradigms, and can be helpful, neutral, or harmful, according to circumstance. Although there has been less careful or analytical study of it in humans, it can be interpreted as underpinning a wealth of behavioral aberrations. © 2009 Elsevier Inc. All rights reserved.

Robust design optimization of gas turbine compression systems

Gas turbine compression systems are required to perform adequately over a range of operating conditions. Complexity has encouraged the conventional design process for compressors to focus initially on one operating point, usually the most commonor arduous, to draw up an outline design. Generally, only as this initial design is refined is its offdesign performance assessed in detail. Not only does this necessarily introduce a potentially costly and timeconsuming extra loop in the design process, but it also may result in a design whose offdesign behavior is suboptimal. Aversion of nonintrusive polynomial chaos was previously developed in which a set of orthonormal polynomials was generated to facilitate a rapid analysis of robustness in the presence of generic uncertainties with good accuracy. In this paper, this analysis method is incorporated in real time into the design process for the compression system of a three-shaft gas turbine aeroengine. This approach to robust optimization is shown to lead to designs that exhibit consistently improved system performance with reduced sensitivity to offdesign operation.

A reason for unreason: returns-based beliefs in game theory

Players cooperate in experiments more than game theory would predict. We introduce the ‘returns-based beliefs’ approach: the expected returns of a particular strategy in proportion to total expected returns of all strategies. Using a decision analytic solution concept, Luce’s (1959) probabilistic choice model, and ‘hyperpriors’ for ambiguity in players’ cooperability, our approach explains empirical observations in various classes of games including the Prisoner’s and Traveler’s Dilemmas. Testing the closeness of fit of our model on Selten and Chmura (2008) data for completely mixed 2 × 2 games shows that with loss aversion, returns-based beliefs explain the data better than other equilibrium concepts.

Graduate Education for Leadership in Sustainable Development Innovation , Practice and Research

This paper reflects on the motivation, method and effectiveness of teaching leadership and organisational change to graduate engineers. Delivering progress towards sustainable development requires engineers who are aware of pressing global issues (such as resource depletion, climate change, social inequity and an interdependent economy) since it is they who deliver the goods and services that underpin society within these constraints. In recognition of this fact the Cambridge University MPhil in Engineering for Sustainable Development has focussed on educating engineers to become effective change agents in their professional field with the confidence to challenge orthodoxy in adopting traditional engineering solutions. This paper reflects on ten years of delivering this course to review how teaching change management and leadership aspects of the programme have evolved and progressed over that time. As the students on this professional practice have often extensive experience as practising engineers and scientists, they have learned the limitations of their technical background when solving complex problems. Students often join the course recognising their need to broaden their knowledge of relevant cross-disciplinary skills. The course offers an opportunity for these early to mid-career engineers to explore an ethical and value-based approach to bringing about effective change in their particular sectors and organisations. This is achieved through action learning assignments in combination with reflections on the theory of change to enable students to equip themselves with tools that help them to be effective in making their professional and personal life choices. This paper draws on feedback gathered from students during their participation on the course and augments this with alumni reflections gathered some years after their graduation. These professionals are able to look back on their experience of the taught components and reflect on how they have been able to apply this key learning in their subsequent careers.

Graduate education for leadership and organisational change in sustainable development

This paper reflects on the motivation, method and effectiveness of teaching leadership and organisational change to graduate engineers. Delivering progress towards sustainable development requires engineers who are aware of pressing global issues (such as resource depletion, climate change, social inequity and an interdependent economy) since it is they who deliver the goods and services that underpin society within these constraints. They also must understand how to implement change in the organisations within which they will work. In recognition of this fact the Cambridge University MPhil in Engineering for Sustainable Development has focussed on educating engineers to become effective change agents in their professional field with the confidence to challenge orthodoxy in adopting traditional engineering solutions. This paper reflects on ten years of delivering a special module to review how teaching change management and leadership aspects of the programme have evolved and progressed over that time. As the students who embark on this professional practice have often extensive experience as practising engineers and scientists, many have already learned the limitations of their technical background when solving complex problems. Students often join the course recognising their need to broaden their knowledge of relevant cross-disciplinary skills. The programme offers an opportunity for these early to mid-career engineers to explore an ethical and value-based approach to bringing about effective change in their particular sectors and organisations. This is achieved through action learning assignments in combination with reflections on the theory of change to enable students to equip themselves with tools that help them to be effective in making their professional and personal life choices. This paper draws on feedback gathered from students during their participation on the programme and augments this with alumni reflections gathered some years after their graduation. These professionals are able to look back on their experience of the taught components and reflect on how they have been able to apply this key learning in their subsequent careers. Copyright © 2012 September.

Opponent appetitive-aversive neural processes underlie predictive learning of pain relief.

Termination of a painful or unpleasant event can be rewarding. However, whether the brain treats relief in a similar way as it treats natural reward is unclear, and the neural processes that underlie its representation as a motivational goal remain poorly understood. We used fMRI (functional magnetic resonance imaging) to investigate how humans learn to generate expectations of pain relief. Using a pavlovian conditioning procedure, we show that subjects experiencing prolonged experimentally induced pain can be conditioned to predict pain relief. This proceeds in a manner consistent with contemporary reward-learning theory (average reward/loss reinforcement learning), reflected by neural activity in the amygdala and midbrain. Furthermore, these reward-like learning signals are mirrored by opposite aversion-like signals in lateral orbitofrontal cortex and anterior cingulate cortex. This dual coding has parallels to 'opponent process' theories in psychology and promotes a formal account of prediction and expectation during pain.