An Architecture for Proof Planning Systems

This paper presents a generic architecture for proof planning systems in terms of an interaction between a customisable proof module and search module. These refer to both global and local information contained in reasoning states.

'Artificial Immune Systems Tutorial'

The biological immune system is a robust, complex, adaptive system that defends the body from foreign pathogens. It is able to categorize all cells (or molecules) within the body as self-cells or non-self cells. It does this with the help of a distributed task force that has the intelligence to take action from a local and also a global perspective using its network of chemical messengers for communication. There are two major branches of the immune system. The innate immune system is an unchanging mechanism that detects and destroys certain invading organisms, whilst the adaptive immune system responds to previously unknown foreign cells and builds a response to them that can remain in the body over a long period of time. This remarkable information processing biological system has caught the attention of computer science in recent years. A novel computational intelligence technique, inspired by immunology, has emerged, called Artificial Immune Systems. Several concepts from the immune have been extracted and applied for solution to real world science and engineering problems. In this tutorial, we briefly describe the immune system metaphors that are relevant to existing Artificial Immune Systems methods. We will then show illustrative real-world problems suitable for Artificial Immune Systems and give a step-by-step algorithm walkthrough for one such problem. A comparison of the Artificial Immune Systems to other well-known algorithms, areas for future work, tips & tricks and a list of resources will round this tutorial off. It should be noted that as Artificial Immune Systems is still a young and evolving field, there is not yet a fixed algorithm template and hence actual implementations might differ somewhat from time to time and from those examples given here.

'Artificial Immune Systems Tutorial'

The biological immune system is a robust, complex, adaptive system that defends the body from foreign pathogens. It is able to categorize all cells (or molecules) within the body as self-cells or non-self cells. It does this with the help of a distributed task force that has the intelligence to take action from a local and also a global perspective using its network of chemical messengers for communication. There are two major branches of the immune system. The innate immune system is an unchanging mechanism that detects and destroys certain invading organisms, whilst the adaptive immune system responds to previously unknown foreign cells and builds a response to them that can remain in the body over a long period of time. This remarkable information processing biological system has caught the attention of computer science in recent years. A novel computational intelligence technique, inspired by immunology, has emerged, called Artificial Immune Systems. Several concepts from the immune have been extracted and applied for solution to real world science and engineering problems. In this tutorial, we briefly describe the immune system metaphors that are relevant to existing Artificial Immune Systems methods. We will then show illustrative real-world problems suitable for Artificial Immune Systems and give a step-by-step algorithm walkthrough for one such problem. A comparison of the Artificial Immune Systems to other well-known algorithms, areas for future work, tips & tricks and a list of resources will round this tutorial off. It should be noted that as Artificial Immune Systems is still a young and evolving field, there is not yet a fixed algorithm template and hence actual implementations might differ somewhat from time to time and from those examples given here.

The organization, form and function of intermediate care services and systems in England: results from a national survey

This paper reports the results of a postal survey of intermediate care co-ordinators (ICCs) on the organization and delivery of intermediate care services for older people in England, conducted between November 2003 and May 2004. Questionnaires, which covered a range of issues with a variety of quantitative, ‘tick-box’ and open-ended questions, were returned by 106 respondents, representing just over 35% of primary care trusts (PCTs). We discuss the role of ICCs, the integration of local systems of intermediate care provision, and the form, function and model of delivery of services described by respondents. Using descriptive and statistical analysis of the responses, we highlight in particular the relationship between provision of admission avoidance and supported discharge, the availability of 24-hour care, and the locations in which care is provided, and relate our findings to the emerging evidence base for intermediate care, guidance on implementation from central government, and debate in the literature. Whilst the expansion and integration of intermediate care appear to be continuing apace, much provision seems concentrated in supported discharge services rather than acute admission avoidance, and particularly in residential forms of post-acute intermediate care. Supported discharge services tend to be found in residential settings, while admission avoidance provision tends to be non-residential in nature. Twenty-four hour care in non-residential settings is not available in several responding PCTs. These findings raise questions about the relationship between the implementation of intermediate care and the evidence for and aims of the policy as part of NHS modernization, and the extent to which intermediate care represents a genuinely novel approach to the care and rehabilitation of older people.