PROBABILISTIC RESOURCE ALLOCATION SYSTEM WITH SELF-ADAPTIVE CAPABILITY

摘要

A probabilistic resource allocation system is disclosed containing a low capacity computational module STM (30) and a self-organizing associative network LTM (20) where nodes represent resources, terminal end nodes represent goals, and weighted links represent order of resource association. Goals and their priorities are indicated by the user, and allocation decisions are made in STM, while association of resources are supplied by LTM based on the association strength. Weights are assigned to network links based on the frequency and relative success in the previous decision. Accumulation of allocation history within LTM reduces computational demands on subsequent allocations. The network automatically partition itself into strongly associated packets allowing fast approximate computation and display of allocation solutions satisfying the overall reliability and other user-imposed constraints. System performance improves over time based on the performance feedback.