Abstract- Seeding the population of an evolutionary algorithm with solutions from previous runs has proved to be useful when learning control strategies for agents operating in a c...
Mitchell A. Potter, R. Paul Wiegand, H. Joseph Blu...
Case-based problem-solving systems reason and learn from experiences, building up case libraries of problems and solutions to guide future reasoning. The expected bene ts of this l...
When an evolutionary algorithm addresses a sequence of instances of the same problem, it can seed its population with solutions that it found for previous instances. This techniqu...
We generalize the solution of a multicriterial optimization problem which has been given in [5]. They have used a comparison of the criterion fuzzy preference relations and the ge...
Multi-case-base reasoning (MCBR) extends case-based reasoning to draw on multiple case bases that may address somewhat different tasks. In MCBR, an agent selectively supplements i...