A Functional Architecture Approach to Neural Systems

The technology for the design of systems to perform extremely complex combinations of real-time functionality has developed over a long period. This technology is based on the use of a hardware architecture with a physical separation into memory and processing, and a software architecture which divides functionality into a disciplined hierarchy of software components which exchange unambiguous information. This technology experiences difficulty in design of systems to perform parallel processing, and extreme difficulty in design of systems which can heuristically change their own functionality. These limitations derive from the approach to information exchange between functional components. A design approach in which functional components can exchange ambiguous information leads to systems with the recommendation architecture which are less subject to these limitations. Biological brains have been constrained by natural pressures to adopt functional architectures with this different information exchange approach. Neural networks have not made a complete shift to use of ambiguous information, and do not address adequate management of context for ambiguous information exchange between modules. As a result such networks cannot be scaled to complex functionality. Simulations of systems with the recommendation architecture demonstrate the capability to heuristically organize to perform complex functionality

Market-based Recommendation: Agents that Compete for Consumer Attention

The amount of attention space available for recommending suppliers to consumers on e-commerce sites is typically limited. We present a competitive distributed recommendation mechanism based on adaptive software agents for efficiently allocating the 'consumer attention space', or banners. In the example of an electronic shopping mall, the task is delegated to the individual shops, each of which evaluates the information that is available about the consumer and his or her interests (e.g. keywords, product queries, and available parts of a profile). Shops make a monetary bid in an auction where a limited amount of 'consumer attention space' for the arriving consumer is sold. Each shop is represented by a software agent that bids for each consumer. This allows shops to rapidly adapt their bidding strategy to focus on consumers interested in their offerings. For various basic and simple models for on-line consumers, shops, and profiles, we demonstrate the feasibility of our system by evolutionary simulations as in the field of agent-based computational economics (ACE). We also develop adaptive software agents that learn bidding strategies, based on neural networks and strategy exploration heuristics. Furthermore, we address the commercial and technological advantages of this distributed market-based approach. The mechanism we describe is not limited to the example of the electronic shopping mall, but can easily be extended to other domains

The Influence of Corporate Social Responsibility Activity Toward Customer Loyalty Through Improvement of Quality of Life in Urban Area

The success of Corporate Social Responsibility (CSR) activities can create competitive advantage by influencing customer responses to firms’ offering. Customer’s awareness of CSR activity will influence their loyalty through their perception that activity can improve society’s quality of life where the CSR activities were implemented. The objective of this study is to evaluate the relationship between CSR awareness and loyalty that mediated by CSR Belief, Company Ability Belief, Quality of Life, and Company Reputation using Structural Equation Modelling (SEM). The result shows little differrences among five firms/brands as the object of the research, that are beverage, soap, car, lubricant, and cigarette. This result has an implication for the firm that CSR activities are not just cost center activities, but also can create reputation, and in the long run can create customer loyalty that contributes to firm’s financial benefit

Eastern Suffolk BOCES and Eastern Suffolk Civil Service Unit, United Public Service Employees Union (UPSEU)

In the matter of the fact-finding between the Eastern Suffolk BOCES, employer, and the Eastern Suffolk Civil Service Unit, United Public Service Employees Union (UPSEU), union. PERB case no. M2011-335. Before: Thomas J. Linden, fact finder