EPISTEMIC FOUNDATIONS OF SOLUTION CONCEPTS IN GAME THEORY: AN INTRODUCTION

We give an introduction to the literature on the epistemic foundations of solution concepts in game theory. Only normal-form games are considered. The solution concepts analyzed are rationalizability, strong rationalizability, correlated equilibrium and Nash equilibrium. The analysis is carried out locally in terms of properties of the belief hierarchies. Several examples are used throughout to illustrate definitions and concepts.

A situation-response model for intelligent pilot aiding

An intelligent pilot aiding system needs models of the pilot information processing to provide the computational basis for successful cooperation between the pilot and the aiding system. By combining artificial intelligence concepts with the human information processing model of Rasmussen, an abstraction hierarchy of states of knowledge, processing functions, and shortcuts are developed, which is useful for characterizing the information processing both of the pilot and of the aiding system. This approach is used in the conceptual design of a real time intelligent aiding system for flight crews of transport aircraft. One promising result was the tentative identification of a particular class of information processing shortcuts, from situation characterizations to appropriate responses, as the most important reliable pathway for dealing with complex time critical situations

Flight crew aiding for recovery from subsystem failures

Some of the conceptual issues associated with pilot aiding systems are discussed and an implementation of one component of such an aiding system is described. It is essential that the format and content of the information the aiding system presents to the crew be compatible with the crew's mental models of the task. It is proposed that in order to cooperate effectively, both the aiding system and the flight crew should have consistent information processing models, especially at the point of interface. A general information processing strategy, developed by Rasmussen, was selected to serve as the bridge between the human and aiding system's information processes. The development and implementation of a model-based situation assessment and response generation system for commercial transport aircraft are described. The current implementation is a prototype which concentrates on engine and control surface failure situations and consequent flight emergencies. The aiding system, termed Recovery Recommendation System (RECORS), uses a causal model of the relevant subset of the flight domain to simulate the effects of these failures and to generate appropriate responses, given the current aircraft state and the constraints of the current flight phase. Since detailed information about the aircraft state may not always be available, the model represents the domain at varying levels of abstraction and uses the less detailed abstraction levels to make inferences when exact information is not available. The structure of this model is described in detail

Analysing children's accounts using discourse analysis

Discourse analytic approaches to research depart from understandings of the individual and of the relation between language and knowledge provided by positivist and post-positivist approaches. This chapter sets out to show what this might mean for studying children’s experiences through, for example, interview-based research, and how a discourse analytic approach may bring into play conceptual resources that are particularly valuable for research with children. First and foremost, discursive approaches highlight the interpretive nature of any research, not only that with children. As a consequence, they challenge the conventional distinction between data collection and analysis, question the status of research accounts and encourage us to question taken-for-granted assumptions about distinctions between adults and children. Hence our emphasis in this chapter is on the active and subjective involvement of researchers in hearing, interpreting and representing children’s ‘voices’

Machine learning and its applications in reliability analysis systems

In this thesis, we are interested in exploring some aspects of Machine Learning (ML) and its application in the Reliability Analysis systems (RAs). We begin by investigating some ML paradigms and their- techniques, go on to discuss the possible applications of ML in improving RAs performance, and lastly give guidelines of the architecture of learning RAs. Our survey of ML covers both levels of Neural Network learning and Symbolic learning. In symbolic process learning, five types of learning and their applications are discussed: rote learning, learning from instruction, learning from analogy, learning from examples, and learning from observation and discovery. The Reliability Analysis systems (RAs) presented in this thesis are mainly designed for maintaining plant safety supported by two functions: risk analysis function, i.e., failure mode effect analysis (FMEA) ; and diagnosis function, i.e., real-time fault location (RTFL). Three approaches have been discussed in creating the RAs. According to the result of our survey, we suggest currently the best design of RAs is to embed model-based RAs, i.e., MORA (as software) in a neural network based computer system (as hardware). However, there are still some improvement which can be made through the applications of Machine Learning. By implanting the 'learning element', the MORA will become learning MORA (La MORA) system, a learning Reliability Analysis system with the power of automatic knowledge acquisition and inconsistency checking, and more. To conclude our thesis, we propose an architecture of La MORA

Reasoning with visual knowledge in an object recognition system

The impact of artificial intelligence on computer vision has provided various perspectives and approaches to solving problems of the human visual system. Some of the symbolic processing and knowledge-based techniques implemented in vision systems represent a meaningful extension to the low-level, algorithmic processing which has been emphasized since the advent of the computer vision field. The higher-level processes attempt to capture the essence of visual cognition, specifically by encompassing a model of the visual world and the reasoning processes that manipulate this stored visual knowledge and environmental cues. This thesis includes a discussion of existing computer vision systems surveyed from a high-level perspective. The goal of this thesis is to develop a high-level inference system that implements reasoning processes and utilizes a visual memory model to achieve object recognition in a specific domain. The focus is on symbolically representing and reasoning with high-level knowledge using a frame-based approach. The organization and structuring of domain knowledge, reasoning processes and control and search strategies are emphasized. The implementation utilizes a frame package written in Prolog

Negotiating and enabling spaces for gender justice

Through feminist informed understandings of injustice, this paper draws on significant research to re-articulate prevailing issues of gender inequity within and beyond the contexts of education in Australia. Following a location of the unconvincing but pervasive warrant for boys' issues to dominate the gender equity scene, the paper turns to a discussion about locating and leveraging strategic points of intervention for transformative gender just educational policy and practice. New and emerging policy environments, more receptive to educational research, that address issues of economic and cultural marginalisation in new times are argued to offer generative spaces to reinvigorate crucial gender debates associated with post-school pathways and social outcomes. Foregrounding feminist concerns in these areas is presented as central to constructing strong policy frames that can better address issues of gender, economic marginalisation and cultural disadvantage. The paper then turns to a discussion about how radical re-envisionings of curriculum and pedagogy, to reflect issues of distributive and cultural justice, might work to dismantle and transform the inequitable power relations and underlying frameworks that generate gender injustice within and beyond the contexts of education. The paper concludes by illustrating the imperative of drawing on transformative gender justice lenses to evaluate and, in particular, anticipate the limits of particular reform agendas and interventions