Lazy learning is a memory-based technique that, once a query is received, extracts a prediction interpolating locally the neighboring examples of the query which are considered re...
An efficient “Simulation Optimization” technique is developed to solve system design problems which can not be expressed in explicit analytical or mathematical models. In part...
There are many planning applications that require an agent to coordinate its activities with processes that change continuously over time. Several proposals have been made for com...
This paper describes a learning system, LASSY1, which explores domains represented by Prolog databases, and use its acquired knowledge to increase the efficiency of a Prolog inter...
Several areas of multi-agent research, such as large-scale agent organization and experience-based decision making, demand novel perspectives and efficient approaches for multisca...