Semiotic Dynamics Solves the Symbol Grounding Problem

Language requires the capacity to link symbols (words, sentences) through the intermediary of internal representations to the physical world, a process known as symbol grounding. One of the biggest debates in the cognitive sciences concerns the question how human brains are able to do this. Do we need a material explanation or a system explanation? John Searle's well known Chinese Room thought experiment, which continues to generate a vast polemic literature of arguments and counter-arguments, has argued that autonomously establishing internal representations of the world (called 'intentionality' in philosophical parlance) is based on special properties of human neural tissue and that consequently an artificial system, such as an autonomous physical robot, can never achieve this. Here we study the Grounded Naming Game as a particular example of symbolic interaction and investigate a dynamical system that autonomously builds up and uses the semiotic networks necessary for performance in the game. We demonstrate in real experiments with physical robots that such a dynamical system indeed leads to a successful emergent communication system and hence that symbol grounding and intentionality can be explained in terms of a particular kind of system dynamics. The human brain has obviously the right mechanisms to participate in this kind of dynamics but the same dynamics can also be embodied in other types of physical systems

Ensuring cost-effective heat exchanger network design for non-continuous processes

The variation in stream conditions over time inevitably adds significant complexity to the task of integrating non-continuous processes. The Time Averaging Method (TAM), where stream conditions are simply averaged across the entire time cycle, leads to unrealistic energy targets for direct heat recovery and consequently to Heat Exchanger Network (HEN) designs that are in fact suboptimal. This realisation led to the development of the Time Slice Method (TSM) that instead considers each time interval separately, and can be used to reach accurate targets and to design the appropriate HEN to maximise heat recovery. However, in practise the HENs often require excessive exchanger surface area, which renders them unfeasible when capital costs are taken in to account. An extension of the TSM that reduces the required overall exchanger surface area and systematically distributes it across the stream matches is proposed. The methodology is summarised with the help of a simple case study and further improvement opportunities are discusse

Carbon Emissions Pinch Analysis (CEPA) for emissions reduction in the New Zealand electricity sector

Carbon Emissions Pinch Analysis (CEPA) is a recent extension of traditional thermal and mass pinch analysis to the area of emissions targeting and planning on a macro-scale (i.e. economy wide). This paper presents an extension to the current methodology that accounts for increased demand and a carbon pinch analysis of the New Zealand electricity industry while illustrating some of the issues with realising meaningful emissions reductions. The current large proportion of renewable generation (67% in 2007) complicates extensive reduction of carbon emissions from electricity generation. The largest growth in renewable generation is expected to come from geothermal generation followed by wind and hydro. A four fold increase in geothermal generation capacity is needed in addition to large amounts of new wind generation to reduce emissions to around 1990 levels and also meet projected demand. The expected expansion of geothermal generation in New Zealand raises issues of GHG emissions from the geothermal fields. The emissions factors between fields can vary by almost two orders of magnitude making predictions of total emissions highly site specific